Overview

Dataset statistics

Number of variables87
Number of observations20000
Missing cells573470
Missing cells (%)33.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.3 MiB
Average record size in memory696.0 B

Variable types

Numeric77
Categorical10

Alerts

HR-min is highly correlated with HR-maxHigh correlation
HR-max is highly correlated with HR-minHigh correlation
SBP-min is highly correlated with MAP-min and 1 other fieldsHigh correlation
SBP-max is highly correlated with MAP-max and 1 other fieldsHigh correlation
MAP-min is highly correlated with SBP-min and 1 other fieldsHigh correlation
MAP-max is highly correlated with SBP-max and 1 other fieldsHigh correlation
DBP-min is highly correlated with SBP-min and 1 other fieldsHigh correlation
DBP-max is highly correlated with SBP-max and 1 other fieldsHigh correlation
EtCO2-min is highly correlated with EtCO2-maxHigh correlation
EtCO2-max is highly correlated with EtCO2-minHigh correlation
BaseExcess-min is highly correlated with BaseExcess-max and 2 other fieldsHigh correlation
BaseExcess-max is highly correlated with BaseExcess-min and 2 other fieldsHigh correlation
HCO3-min is highly correlated with BaseExcess-min and 3 other fieldsHigh correlation
HCO3-max is highly correlated with BaseExcess-max and 1 other fieldsHigh correlation
FiO2-min is highly correlated with FiO2-maxHigh correlation
FiO2-max is highly correlated with FiO2-minHigh correlation
pH-min is highly correlated with BaseExcess-min and 2 other fieldsHigh correlation
pH-max is highly correlated with PaCO2-minHigh correlation
PaCO2-min is highly correlated with pH-max and 1 other fieldsHigh correlation
PaCO2-max is highly correlated with pH-min and 1 other fieldsHigh correlation
SaO2-min is highly correlated with SaO2-maxHigh correlation
SaO2-max is highly correlated with SaO2-minHigh correlation
AST-min is highly correlated with AST-maxHigh correlation
AST-max is highly correlated with AST-minHigh correlation
BUN-min is highly correlated with BUN-max and 2 other fieldsHigh correlation
BUN-max is highly correlated with BUN-min and 2 other fieldsHigh correlation
Alkalinephos-min is highly correlated with Alkalinephos-maxHigh correlation
Alkalinephos-max is highly correlated with Alkalinephos-minHigh correlation
Calcium-min is highly correlated with Calcium-maxHigh correlation
Calcium-max is highly correlated with Calcium-minHigh correlation
Chloride-min is highly correlated with Chloride-maxHigh correlation
Chloride-max is highly correlated with Chloride-minHigh correlation
Creatinine-min is highly correlated with BUN-min and 2 other fieldsHigh correlation
Creatinine-max is highly correlated with BUN-min and 2 other fieldsHigh correlation
Bilirubin_direct-min is highly correlated with Bilirubin_direct-max and 2 other fieldsHigh correlation
Bilirubin_direct-max is highly correlated with Bilirubin_direct-min and 2 other fieldsHigh correlation
Lactate-min is highly correlated with Lactate-maxHigh correlation
Lactate-max is highly correlated with Lactate-minHigh correlation
Phosphate-min is highly correlated with Phosphate-maxHigh correlation
Phosphate-max is highly correlated with Phosphate-minHigh correlation
Bilirubin_total-min is highly correlated with Bilirubin_direct-min and 2 other fieldsHigh correlation
Bilirubin_total-max is highly correlated with Bilirubin_direct-min and 2 other fieldsHigh correlation
TroponinI-min is highly correlated with TroponinI-maxHigh correlation
TroponinI-max is highly correlated with TroponinI-minHigh correlation
Hct-min is highly correlated with Hct-max and 2 other fieldsHigh correlation
Hct-max is highly correlated with Hct-min and 2 other fieldsHigh correlation
Hgb-min is highly correlated with Hct-min and 2 other fieldsHigh correlation
Hgb-max is highly correlated with Hct-min and 2 other fieldsHigh correlation
PTT-min is highly correlated with PTT-maxHigh correlation
PTT-max is highly correlated with PTT-minHigh correlation
WBC-min is highly correlated with WBC-maxHigh correlation
WBC-max is highly correlated with WBC-minHigh correlation
Fibrinogen-min is highly correlated with Fibrinogen-maxHigh correlation
Fibrinogen-max is highly correlated with Fibrinogen-minHigh correlation
Platelets-min is highly correlated with Platelets-maxHigh correlation
Platelets-max is highly correlated with Platelets-minHigh correlation
Age-min is highly correlated with Age-maxHigh correlation
Age-max is highly correlated with Age-minHigh correlation
Gender-min is highly correlated with Gender-maxHigh correlation
Gender-max is highly correlated with Gender-minHigh correlation
Unit1-min is highly correlated with Unit1-max and 2 other fieldsHigh correlation
Unit1-max is highly correlated with Unit1-min and 2 other fieldsHigh correlation
Unit2-min is highly correlated with Unit1-min and 2 other fieldsHigh correlation
Unit2-max is highly correlated with Unit1-min and 2 other fieldsHigh correlation
HospAdmTime-min is highly correlated with HospAdmTime-maxHigh correlation
HospAdmTime-max is highly correlated with HospAdmTime-minHigh correlation
ICULOS-max is highly correlated with Hours-min and 1 other fieldsHigh correlation
SepsisLabel-max is highly correlated with Sepsis-min and 1 other fieldsHigh correlation
Sepsis-min is highly correlated with SepsisLabel-max and 1 other fieldsHigh correlation
Sepsis-max is highly correlated with SepsisLabel-max and 1 other fieldsHigh correlation
Hours-min is highly correlated with ICULOS-max and 1 other fieldsHigh correlation
Hours-max is highly correlated with ICULOS-max and 1 other fieldsHigh correlation
HR-min is highly correlated with HR-maxHigh correlation
HR-max is highly correlated with HR-minHigh correlation
SBP-min is highly correlated with MAP-min and 1 other fieldsHigh correlation
SBP-max is highly correlated with MAP-max and 1 other fieldsHigh correlation
MAP-min is highly correlated with SBP-min and 1 other fieldsHigh correlation
MAP-max is highly correlated with SBP-max and 1 other fieldsHigh correlation
DBP-min is highly correlated with SBP-min and 1 other fieldsHigh correlation
DBP-max is highly correlated with SBP-max and 1 other fieldsHigh correlation
EtCO2-min is highly correlated with EtCO2-maxHigh correlation
EtCO2-max is highly correlated with EtCO2-minHigh correlation
BaseExcess-min is highly correlated with BaseExcess-max and 4 other fieldsHigh correlation
BaseExcess-max is highly correlated with BaseExcess-min and 2 other fieldsHigh correlation
HCO3-min is highly correlated with BaseExcess-min and 4 other fieldsHigh correlation
HCO3-max is highly correlated with BaseExcess-min and 2 other fieldsHigh correlation
pH-min is highly correlated with BaseExcess-min and 1 other fieldsHigh correlation
PaCO2-min is highly correlated with PaCO2-max and 1 other fieldsHigh correlation
PaCO2-max is highly correlated with PaCO2-minHigh correlation
AST-min is highly correlated with AST-maxHigh correlation
AST-max is highly correlated with AST-minHigh correlation
BUN-min is highly correlated with BUN-max and 3 other fieldsHigh correlation
BUN-max is highly correlated with BUN-min and 3 other fieldsHigh correlation
Alkalinephos-min is highly correlated with Alkalinephos-maxHigh correlation
Alkalinephos-max is highly correlated with Alkalinephos-minHigh correlation
Chloride-min is highly correlated with Chloride-maxHigh correlation
Chloride-max is highly correlated with PaCO2-min and 1 other fieldsHigh correlation
Creatinine-min is highly correlated with BUN-min and 4 other fieldsHigh correlation
Creatinine-max is highly correlated with BUN-min and 4 other fieldsHigh correlation
Bilirubin_direct-min is highly correlated with Bilirubin_direct-max and 2 other fieldsHigh correlation
Bilirubin_direct-max is highly correlated with Bilirubin_direct-min and 2 other fieldsHigh correlation
Lactate-min is highly correlated with Lactate-maxHigh correlation
Lactate-max is highly correlated with BaseExcess-min and 2 other fieldsHigh correlation
Magnesium-min is highly correlated with Magnesium-maxHigh correlation
Magnesium-max is highly correlated with Magnesium-minHigh correlation
Phosphate-min is highly correlated with BUN-min and 3 other fieldsHigh correlation
Phosphate-max is highly correlated with BUN-max and 3 other fieldsHigh correlation
Bilirubin_total-min is highly correlated with Bilirubin_direct-min and 2 other fieldsHigh correlation
Bilirubin_total-max is highly correlated with Bilirubin_direct-min and 2 other fieldsHigh correlation
TroponinI-min is highly correlated with TroponinI-maxHigh correlation
TroponinI-max is highly correlated with TroponinI-minHigh correlation
Hct-min is highly correlated with Hct-max and 2 other fieldsHigh correlation
Hct-max is highly correlated with Hct-min and 2 other fieldsHigh correlation
Hgb-min is highly correlated with Hct-min and 2 other fieldsHigh correlation
Hgb-max is highly correlated with Hct-min and 2 other fieldsHigh correlation
PTT-min is highly correlated with PTT-maxHigh correlation
PTT-max is highly correlated with PTT-minHigh correlation
WBC-min is highly correlated with WBC-maxHigh correlation
WBC-max is highly correlated with WBC-minHigh correlation
Fibrinogen-min is highly correlated with Fibrinogen-maxHigh correlation
Fibrinogen-max is highly correlated with Fibrinogen-minHigh correlation
Platelets-min is highly correlated with Platelets-maxHigh correlation
Platelets-max is highly correlated with Platelets-minHigh correlation
Age-min is highly correlated with Age-maxHigh correlation
Age-max is highly correlated with Age-minHigh correlation
Gender-min is highly correlated with Gender-maxHigh correlation
Gender-max is highly correlated with Gender-minHigh correlation
Unit1-min is highly correlated with Unit1-max and 2 other fieldsHigh correlation
Unit1-max is highly correlated with Unit1-min and 2 other fieldsHigh correlation
Unit2-min is highly correlated with Unit1-min and 2 other fieldsHigh correlation
Unit2-max is highly correlated with Unit1-min and 2 other fieldsHigh correlation
HospAdmTime-min is highly correlated with HospAdmTime-maxHigh correlation
HospAdmTime-max is highly correlated with HospAdmTime-minHigh correlation
ICULOS-max is highly correlated with Hours-min and 1 other fieldsHigh correlation
SepsisLabel-max is highly correlated with Sepsis-min and 1 other fieldsHigh correlation
Sepsis-min is highly correlated with SepsisLabel-max and 1 other fieldsHigh correlation
Sepsis-max is highly correlated with SepsisLabel-max and 1 other fieldsHigh correlation
Hours-min is highly correlated with ICULOS-max and 1 other fieldsHigh correlation
Hours-max is highly correlated with ICULOS-max and 1 other fieldsHigh correlation
SBP-min is highly correlated with MAP-minHigh correlation
SBP-max is highly correlated with MAP-maxHigh correlation
MAP-min is highly correlated with SBP-min and 1 other fieldsHigh correlation
MAP-max is highly correlated with SBP-max and 1 other fieldsHigh correlation
DBP-min is highly correlated with MAP-minHigh correlation
DBP-max is highly correlated with MAP-maxHigh correlation
BaseExcess-min is highly correlated with HCO3-minHigh correlation
BaseExcess-max is highly correlated with HCO3-maxHigh correlation
HCO3-min is highly correlated with BaseExcess-minHigh correlation
HCO3-max is highly correlated with BaseExcess-maxHigh correlation
FiO2-min is highly correlated with FiO2-maxHigh correlation
FiO2-max is highly correlated with FiO2-minHigh correlation
AST-min is highly correlated with AST-maxHigh correlation
AST-max is highly correlated with AST-minHigh correlation
BUN-min is highly correlated with BUN-max and 1 other fieldsHigh correlation
BUN-max is highly correlated with BUN-min and 1 other fieldsHigh correlation
Alkalinephos-min is highly correlated with Alkalinephos-maxHigh correlation
Alkalinephos-max is highly correlated with Alkalinephos-minHigh correlation
Chloride-min is highly correlated with Chloride-maxHigh correlation
Chloride-max is highly correlated with Chloride-minHigh correlation
Creatinine-min is highly correlated with BUN-min and 1 other fieldsHigh correlation
Creatinine-max is highly correlated with BUN-max and 1 other fieldsHigh correlation
Bilirubin_direct-min is highly correlated with Bilirubin_direct-max and 2 other fieldsHigh correlation
Bilirubin_direct-max is highly correlated with Bilirubin_direct-min and 2 other fieldsHigh correlation
Lactate-min is highly correlated with Lactate-maxHigh correlation
Lactate-max is highly correlated with Lactate-minHigh correlation
Phosphate-min is highly correlated with Phosphate-maxHigh correlation
Phosphate-max is highly correlated with Phosphate-minHigh correlation
Bilirubin_total-min is highly correlated with Bilirubin_direct-min and 2 other fieldsHigh correlation
Bilirubin_total-max is highly correlated with Bilirubin_direct-min and 2 other fieldsHigh correlation
TroponinI-min is highly correlated with TroponinI-maxHigh correlation
TroponinI-max is highly correlated with TroponinI-minHigh correlation
Hct-min is highly correlated with Hct-max and 2 other fieldsHigh correlation
Hct-max is highly correlated with Hct-min and 2 other fieldsHigh correlation
Hgb-min is highly correlated with Hct-min and 2 other fieldsHigh correlation
Hgb-max is highly correlated with Hct-min and 2 other fieldsHigh correlation
PTT-min is highly correlated with PTT-maxHigh correlation
PTT-max is highly correlated with PTT-minHigh correlation
WBC-min is highly correlated with WBC-maxHigh correlation
WBC-max is highly correlated with WBC-minHigh correlation
Fibrinogen-min is highly correlated with Fibrinogen-maxHigh correlation
Fibrinogen-max is highly correlated with Fibrinogen-minHigh correlation
Platelets-min is highly correlated with Platelets-maxHigh correlation
Platelets-max is highly correlated with Platelets-minHigh correlation
Age-min is highly correlated with Age-maxHigh correlation
Age-max is highly correlated with Age-minHigh correlation
Gender-min is highly correlated with Gender-maxHigh correlation
Gender-max is highly correlated with Gender-minHigh correlation
Unit1-min is highly correlated with Unit1-max and 2 other fieldsHigh correlation
Unit1-max is highly correlated with Unit1-min and 2 other fieldsHigh correlation
Unit2-min is highly correlated with Unit1-min and 2 other fieldsHigh correlation
Unit2-max is highly correlated with Unit1-min and 2 other fieldsHigh correlation
HospAdmTime-min is highly correlated with HospAdmTime-maxHigh correlation
HospAdmTime-max is highly correlated with HospAdmTime-minHigh correlation
ICULOS-max is highly correlated with Hours-min and 1 other fieldsHigh correlation
SepsisLabel-max is highly correlated with Sepsis-min and 1 other fieldsHigh correlation
Sepsis-min is highly correlated with SepsisLabel-max and 1 other fieldsHigh correlation
Sepsis-max is highly correlated with SepsisLabel-max and 1 other fieldsHigh correlation
Hours-min is highly correlated with ICULOS-max and 1 other fieldsHigh correlation
Hours-max is highly correlated with ICULOS-max and 1 other fieldsHigh correlation
SepsisLabel-max is highly correlated with Sepsis-min and 1 other fieldsHigh correlation
Gender-min is highly correlated with Gender-maxHigh correlation
Unit2-max is highly correlated with Unit2-min and 2 other fieldsHigh correlation
Sepsis-min is highly correlated with SepsisLabel-max and 1 other fieldsHigh correlation
Gender-max is highly correlated with Gender-minHigh correlation
Unit2-min is highly correlated with Unit2-max and 2 other fieldsHigh correlation
Unit1-min is highly correlated with Unit2-max and 2 other fieldsHigh correlation
Unit1-max is highly correlated with Unit2-max and 2 other fieldsHigh correlation
Sepsis-max is highly correlated with SepsisLabel-max and 1 other fieldsHigh correlation
EtCO2-min has 16784 (83.9%) missing values Missing
EtCO2-max has 16784 (83.9%) missing values Missing
BaseExcess-min has 19442 (97.2%) missing values Missing
BaseExcess-max has 19442 (97.2%) missing values Missing
HCO3-min has 19584 (97.9%) missing values Missing
HCO3-max has 19584 (97.9%) missing values Missing
FiO2-min has 14178 (70.9%) missing values Missing
FiO2-max has 14178 (70.9%) missing values Missing
pH-min has 14246 (71.2%) missing values Missing
pH-max has 14246 (71.2%) missing values Missing
PaCO2-min has 14221 (71.1%) missing values Missing
PaCO2-max has 14221 (71.1%) missing values Missing
SaO2-min has 14875 (74.4%) missing values Missing
SaO2-max has 14875 (74.4%) missing values Missing
AST-min has 11536 (57.7%) missing values Missing
AST-max has 11536 (57.7%) missing values Missing
BUN-min has 1591 (8.0%) missing values Missing
BUN-max has 1591 (8.0%) missing values Missing
Alkalinephos-min has 11530 (57.6%) missing values Missing
Alkalinephos-max has 11530 (57.6%) missing values Missing
Calcium-min has 1550 (7.8%) missing values Missing
Calcium-max has 1550 (7.8%) missing values Missing
Chloride-min has 18383 (91.9%) missing values Missing
Chloride-max has 18383 (91.9%) missing values Missing
Creatinine-min has 1588 (7.9%) missing values Missing
Creatinine-max has 1588 (7.9%) missing values Missing
Bilirubin_direct-min has 18529 (92.6%) missing values Missing
Bilirubin_direct-max has 18529 (92.6%) missing values Missing
Glucose-min has 1173 (5.9%) missing values Missing
Glucose-max has 1173 (5.9%) missing values Missing
Lactate-min has 15240 (76.2%) missing values Missing
Lactate-max has 15240 (76.2%) missing values Missing
Magnesium-min has 3543 (17.7%) missing values Missing
Magnesium-max has 3543 (17.7%) missing values Missing
Phosphate-min has 8365 (41.8%) missing values Missing
Phosphate-max has 8365 (41.8%) missing values Missing
Potassium-min has 1434 (7.2%) missing values Missing
Potassium-max has 1434 (7.2%) missing values Missing
Bilirubin_total-min has 11522 (57.6%) missing values Missing
Bilirubin_total-max has 11522 (57.6%) missing values Missing
TroponinI-min has 13436 (67.2%) missing values Missing
TroponinI-max has 13436 (67.2%) missing values Missing
Hct-min has 1953 (9.8%) missing values Missing
Hct-max has 1953 (9.8%) missing values Missing
Hgb-min has 1941 (9.7%) missing values Missing
Hgb-max has 1941 (9.7%) missing values Missing
PTT-min has 15602 (78.0%) missing values Missing
PTT-max has 15602 (78.0%) missing values Missing
WBC-min has 2000 (10.0%) missing values Missing
WBC-max has 2000 (10.0%) missing values Missing
Fibrinogen-min has 18052 (90.3%) missing values Missing
Fibrinogen-max has 18052 (90.3%) missing values Missing
Platelets-min has 1992 (10.0%) missing values Missing
Platelets-max has 1992 (10.0%) missing values Missing
Unit1-min has 6095 (30.5%) missing values Missing
Unit1-max has 6095 (30.5%) missing values Missing
Unit2-min has 6095 (30.5%) missing values Missing
Unit2-max has 6095 (30.5%) missing values Missing
FiO2-min is highly skewed (γ1 = -50.73903075) Skewed
FiO2-max is highly skewed (γ1 = 76.2985385) Skewed
PatientID is uniformly distributed Uniform
PatientID has unique values Unique
HospAdmTime-min has 1145 (5.7%) zeros Zeros
HospAdmTime-max has 1145 (5.7%) zeros Zeros

Reproduction

Analysis started2021-11-29 10:30:52.624500
Analysis finished2021-11-29 10:31:08.038210
Duration15.41 seconds
Software versionpandas-profiling v3.1.1
Download configurationconfig.json

Variables

PatientID
Real number (ℝ≥0)

UNIFORM
UNIQUE

Distinct20000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean110000.5
Minimum100001
Maximum120000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:08.086705image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum100001
5-th percentile101000.95
Q1105000.75
median110000.5
Q3115000.25
95-th percentile119000.05
Maximum120000
Range19999
Interquartile range (IQR)9999.5

Descriptive statistics

Standard deviation5773.647028
Coefficient of variation (CV)0.05248746167
Kurtosis-1.2
Mean110000.5
Median Absolute Deviation (MAD)5000
Skewness0
Sum2200010000
Variance33335000
MonotonicityStrictly increasing
2021-11-29T11:31:08.192992image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1000011
 
< 0.1%
1133311
 
< 0.1%
1133381
 
< 0.1%
1133371
 
< 0.1%
1133361
 
< 0.1%
1133351
 
< 0.1%
1133341
 
< 0.1%
1133331
 
< 0.1%
1133321
 
< 0.1%
1133301
 
< 0.1%
Other values (19990)19990
> 99.9%
ValueCountFrequency (%)
1000011
< 0.1%
1000021
< 0.1%
1000031
< 0.1%
1000041
< 0.1%
1000051
< 0.1%
1000061
< 0.1%
1000071
< 0.1%
1000081
< 0.1%
1000091
< 0.1%
1000101
< 0.1%
ValueCountFrequency (%)
1200001
< 0.1%
1199991
< 0.1%
1199981
< 0.1%
1199971
< 0.1%
1199961
< 0.1%
1199951
< 0.1%
1199941
< 0.1%
1199931
< 0.1%
1199921
< 0.1%
1199911
< 0.1%

HR-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct197
Distinct (%)1.0%
Missing4
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean69.45094019
Minimum20
Maximum154.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:08.303370image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile48
Q160
median68
Q378
95-th percentile94
Maximum154.5
Range134.5
Interquartile range (IQR)18

Descriptive statistics

Standard deviation14.23210391
Coefficient of variation (CV)0.2049231281
Kurtosis0.5554990009
Mean69.45094019
Median Absolute Deviation (MAD)9
Skewness0.4629014619
Sum1388741
Variance202.5527818
MonotonicityNot monotonic
2021-11-29T11:31:08.408769image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
60823
 
4.1%
68676
 
3.4%
62672
 
3.4%
70643
 
3.2%
66606
 
3.0%
64592
 
3.0%
58561
 
2.8%
80535
 
2.7%
74529
 
2.6%
72522
 
2.6%
Other values (187)13837
69.2%
ValueCountFrequency (%)
203
< 0.1%
212
< 0.1%
222
< 0.1%
231
 
< 0.1%
23.51
 
< 0.1%
241
 
< 0.1%
252
< 0.1%
262
< 0.1%
26.51
 
< 0.1%
272
< 0.1%
ValueCountFrequency (%)
154.51
 
< 0.1%
1461
 
< 0.1%
1361
 
< 0.1%
1341
 
< 0.1%
133.51
 
< 0.1%
1331
 
< 0.1%
132.51
 
< 0.1%
1322
< 0.1%
1303
< 0.1%
128.51
 
< 0.1%

HR-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct250
Distinct (%)1.3%
Missing4
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean101.0054761
Minimum42
Maximum211
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:08.513241image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum42
5-th percentile72
Q187
median100
Q3113
95-th percentile135.625
Maximum211
Range169
Interquartile range (IQR)26

Descriptive statistics

Standard deviation19.5572884
Coefficient of variation (CV)0.1936260206
Kurtosis0.3146285639
Mean101.0054761
Median Absolute Deviation (MAD)13
Skewness0.4659869627
Sum2019705.5
Variance382.4875294
MonotonicityNot monotonic
2021-11-29T11:31:08.613042image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
90541
 
2.7%
96499
 
2.5%
100488
 
2.4%
92479
 
2.4%
102458
 
2.3%
94453
 
2.3%
104444
 
2.2%
98435
 
2.2%
106409
 
2.0%
84405
 
2.0%
Other values (240)15385
76.9%
ValueCountFrequency (%)
421
 
< 0.1%
441
 
< 0.1%
451
 
< 0.1%
482
 
< 0.1%
492
 
< 0.1%
502
 
< 0.1%
514
 
< 0.1%
527
< 0.1%
532
 
< 0.1%
5411
0.1%
ValueCountFrequency (%)
2111
 
< 0.1%
1941
 
< 0.1%
1912
< 0.1%
1862
< 0.1%
1842
< 0.1%
182.51
 
< 0.1%
1822
< 0.1%
181.51
 
< 0.1%
1811
 
< 0.1%
1803
< 0.1%

O2Sat-min
Real number (ℝ≥0)

Distinct125
Distinct (%)0.6%
Missing6
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean91.8326748
Minimum20
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:08.719350image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile82.5
Q191
median93
Q395
95-th percentile98
Maximum100
Range80
Interquartile range (IQR)4

Descriptive statistics

Standard deviation6.728730914
Coefficient of variation (CV)0.07327164246
Kurtosis34.74170797
Mean91.8326748
Median Absolute Deviation (MAD)2
Skewness-4.726614861
Sum1836102.5
Variance45.27581971
MonotonicityNot monotonic
2021-11-29T11:31:08.817117image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
942162
10.8%
932161
10.8%
922152
10.8%
952018
10.1%
961666
 
8.3%
911616
 
8.1%
901372
 
6.9%
971183
 
5.9%
89650
 
3.2%
98639
 
3.2%
Other values (115)4375
21.9%
ValueCountFrequency (%)
2012
0.1%
214
 
< 0.1%
224
 
< 0.1%
233
 
< 0.1%
246
< 0.1%
263
 
< 0.1%
271
 
< 0.1%
282
 
< 0.1%
293
 
< 0.1%
303
 
< 0.1%
ValueCountFrequency (%)
100183
 
0.9%
99.526
 
0.1%
99323
 
1.6%
98.538
 
0.2%
98639
 
3.2%
97.577
 
0.4%
971183
5.9%
96.598
 
0.5%
961666
8.3%
95.5119
 
0.6%

O2Sat-max
Real number (ℝ≥0)

Distinct29
Distinct (%)0.1%
Missing6
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean99.49494848
Minimum74
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:08.910102image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum74
5-th percentile97
Q199
median100
Q3100
95-th percentile100
Maximum100
Range26
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.074129091
Coefficient of variation (CV)0.01079581534
Kurtosis49.7162905
Mean99.49494848
Median Absolute Deviation (MAD)0
Skewness-4.482165863
Sum1989302
Variance1.153753304
MonotonicityNot monotonic
2021-11-29T11:31:08.997689image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
10014526
72.6%
992416
 
12.1%
981529
 
7.6%
97650
 
3.2%
96243
 
1.2%
99.5209
 
1.0%
98.5140
 
0.7%
9588
 
0.4%
97.576
 
0.4%
96.539
 
0.2%
Other values (19)78
 
0.4%
ValueCountFrequency (%)
741
 
< 0.1%
791
 
< 0.1%
801
 
< 0.1%
821
 
< 0.1%
831
 
< 0.1%
841
 
< 0.1%
852
< 0.1%
863
< 0.1%
871
 
< 0.1%
892
< 0.1%
ValueCountFrequency (%)
10014526
72.6%
99.5209
 
1.0%
992416
 
12.1%
98.5140
 
0.7%
981529
 
7.6%
97.576
 
0.4%
97650
 
3.2%
96.539
 
0.2%
96243
 
1.2%
95.513
 
0.1%

Temp-min
Real number (ℝ≥0)

Distinct136
Distinct (%)0.7%
Missing49
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean36.0829808
Minimum30
Maximum39.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:09.093040image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile35.15
Q135.8
median36.1
Q336.5
95-th percentile37
Maximum39.2
Range9.2
Interquartile range (IQR)0.7

Descriptive statistics

Standard deviation0.6146643085
Coefficient of variation (CV)0.01703474311
Kurtosis9.011881438
Mean36.0829808
Median Absolute Deviation (MAD)0.3
Skewness-1.324003618
Sum719891.55
Variance0.3778122121
MonotonicityNot monotonic
2021-11-29T11:31:09.191264image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
362163
 
10.8%
36.41415
 
7.1%
36.21399
 
7.0%
36.51320
 
6.6%
36.31304
 
6.5%
36.11258
 
6.3%
35.91142
 
5.7%
35.81039
 
5.2%
36.6961
 
4.8%
35.6920
 
4.6%
Other values (126)7030
35.1%
ValueCountFrequency (%)
303
< 0.1%
30.11
 
< 0.1%
30.41
 
< 0.1%
30.52
< 0.1%
30.61
 
< 0.1%
30.81
 
< 0.1%
30.92
< 0.1%
31.21
 
< 0.1%
31.251
 
< 0.1%
31.31
 
< 0.1%
ValueCountFrequency (%)
39.21
 
< 0.1%
39.11
 
< 0.1%
38.83
< 0.1%
38.73
< 0.1%
38.61
 
< 0.1%
38.52
 
< 0.1%
38.43
< 0.1%
38.35
< 0.1%
38.24
< 0.1%
38.17
< 0.1%

Temp-max
Real number (ℝ≥0)

Distinct117
Distinct (%)0.6%
Missing49
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean37.35684928
Minimum32.6
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:09.290331image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum32.6
5-th percentile36.4
Q136.9
median37.3
Q337.8
95-th percentile38.6
Maximum50
Range17.4
Interquartile range (IQR)0.9

Descriptive statistics

Standard deviation0.7075059994
Coefficient of variation (CV)0.01893912396
Kurtosis11.62398671
Mean37.35684928
Median Absolute Deviation (MAD)0.4
Skewness1.204899895
Sum745306.5
Variance0.5005647391
MonotonicityNot monotonic
2021-11-29T11:31:09.386472image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
371537
 
7.7%
37.21302
 
6.5%
36.81287
 
6.4%
37.11211
 
6.1%
36.91089
 
5.4%
37.41058
 
5.3%
37.51024
 
5.1%
37.61008
 
5.0%
37.31003
 
5.0%
36.7925
 
4.6%
Other values (107)8507
42.5%
ValueCountFrequency (%)
32.61
 
< 0.1%
32.81
 
< 0.1%
33.31
 
< 0.1%
33.51
 
< 0.1%
342
< 0.1%
34.11
 
< 0.1%
34.41
 
< 0.1%
34.51
 
< 0.1%
34.91
 
< 0.1%
353
< 0.1%
ValueCountFrequency (%)
502
< 0.1%
42.11
< 0.1%
41.81
< 0.1%
41.51
< 0.1%
41.42
< 0.1%
41.31
< 0.1%
41.251
< 0.1%
411
< 0.1%
40.91
< 0.1%
40.81
< 0.1%

SBP-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct272
Distinct (%)1.4%
Missing24
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean98.92293402
Minimum20
Maximum183
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:09.488650image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile73
Q187
median97
Q3110
95-th percentile131
Maximum183
Range163
Interquartile range (IQR)23

Descriptive statistics

Standard deviation17.89705432
Coefficient of variation (CV)0.1809191619
Kurtosis0.8313712617
Mean98.92293402
Median Absolute Deviation (MAD)11
Skewness0.239846158
Sum1976084.53
Variance320.3045533
MonotonicityNot monotonic
2021-11-29T11:31:09.586683image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
90540
 
2.7%
92530
 
2.6%
94525
 
2.6%
96495
 
2.5%
91479
 
2.4%
100477
 
2.4%
98469
 
2.3%
102445
 
2.2%
93445
 
2.2%
86443
 
2.2%
Other values (262)15128
75.6%
ValueCountFrequency (%)
204
< 0.1%
212
 
< 0.1%
225
< 0.1%
244
< 0.1%
254
< 0.1%
271
 
< 0.1%
281
 
< 0.1%
291
 
< 0.1%
304
< 0.1%
311
 
< 0.1%
ValueCountFrequency (%)
1831
 
< 0.1%
1711
 
< 0.1%
1681
 
< 0.1%
1673
< 0.1%
1661
 
< 0.1%
1655
< 0.1%
1644
< 0.1%
163.51
 
< 0.1%
1635
< 0.1%
1621
 
< 0.1%

SBP-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct371
Distinct (%)1.9%
Missing24
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean157.0853599
Minimum66
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:09.691095image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum66
5-th percentile117
Q1138
median155
Q3174
95-th percentile203
Maximum300
Range234
Interquartile range (IQR)36

Descriptive statistics

Standard deviation26.80667552
Coefficient of variation (CV)0.1706503746
Kurtosis0.8191790347
Mean157.0853599
Median Absolute Deviation (MAD)18
Skewness0.5269478231
Sum3137937.15
Variance718.5978525
MonotonicityNot monotonic
2021-11-29T11:31:09.791022image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
140344
 
1.7%
156318
 
1.6%
158317
 
1.6%
150314
 
1.6%
164312
 
1.6%
154306
 
1.5%
146306
 
1.5%
148298
 
1.5%
168297
 
1.5%
152293
 
1.5%
Other values (361)16871
84.4%
ValueCountFrequency (%)
662
< 0.1%
701
 
< 0.1%
721
 
< 0.1%
741
 
< 0.1%
751
 
< 0.1%
761
 
< 0.1%
771
 
< 0.1%
791
 
< 0.1%
801
 
< 0.1%
823
< 0.1%
ValueCountFrequency (%)
3001
 
< 0.1%
2991
 
< 0.1%
2981
 
< 0.1%
2963
< 0.1%
2951
 
< 0.1%
2941
 
< 0.1%
2932
< 0.1%
2922
< 0.1%
2902
< 0.1%
2871
 
< 0.1%

MAP-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct177
Distinct (%)0.9%
Missing102
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean68.7824907
Minimum30
Maximum140
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:09.893639image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile50
Q160
median67
Q376
95-th percentile92
Maximum140
Range110
Interquartile range (IQR)16

Descriptive statistics

Standard deviation12.80219302
Coefficient of variation (CV)0.1861257551
Kurtosis0.8476084219
Mean68.7824907
Median Absolute Deviation (MAD)8
Skewness0.4956551988
Sum1368634
Variance163.8961461
MonotonicityNot monotonic
2021-11-29T11:31:10.148510image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
64775
 
3.9%
62761
 
3.8%
68699
 
3.5%
66680
 
3.4%
70670
 
3.4%
60657
 
3.3%
61644
 
3.2%
65641
 
3.2%
63632
 
3.2%
67613
 
3.1%
Other values (167)13126
65.6%
ValueCountFrequency (%)
3010
 
0.1%
3115
0.1%
3218
0.1%
3318
0.1%
349
 
< 0.1%
34.52
 
< 0.1%
3512
0.1%
35.51
 
< 0.1%
3627
0.1%
36.53
 
< 0.1%
ValueCountFrequency (%)
1401
< 0.1%
1361
< 0.1%
1301
< 0.1%
1292
< 0.1%
1261
< 0.1%
1251
< 0.1%
1241
< 0.1%
1231
< 0.1%
122.52
< 0.1%
1222
< 0.1%

MAP-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct343
Distinct (%)1.7%
Missing102
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean110.3982561
Minimum43.5
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:10.250286image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum43.5
5-th percentile83
Q196
median107
Q3120
95-th percentile146
Maximum300
Range256.5
Interquartile range (IQR)24

Descriptive statistics

Standard deviation23.46768543
Coefficient of variation (CV)0.2125729723
Kurtosis13.67664927
Mean110.3982561
Median Absolute Deviation (MAD)12
Skewness2.536329695
Sum2196704.5
Variance550.7322596
MonotonicityNot monotonic
2021-11-29T11:31:10.350217image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100468
 
2.3%
104460
 
2.3%
98455
 
2.3%
96447
 
2.2%
102445
 
2.2%
106434
 
2.2%
108426
 
2.1%
105423
 
2.1%
110423
 
2.1%
103417
 
2.1%
Other values (333)15500
77.5%
ValueCountFrequency (%)
43.51
 
< 0.1%
553
< 0.1%
571
 
< 0.1%
581
 
< 0.1%
602
 
< 0.1%
611
 
< 0.1%
623
< 0.1%
62.51
 
< 0.1%
635
< 0.1%
642
 
< 0.1%
ValueCountFrequency (%)
3004
< 0.1%
2985
< 0.1%
2963
< 0.1%
2951
 
< 0.1%
2944
< 0.1%
2932
 
< 0.1%
2922
 
< 0.1%
2912
 
< 0.1%
2903
< 0.1%
2882
 
< 0.1%

DBP-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct160
Distinct (%)0.8%
Missing27
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean51.84656737
Minimum20
Maximum109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:10.451267image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile35
Q145
median51
Q358
95-th percentile70
Maximum109
Range89
Interquartile range (IQR)13

Descriptive statistics

Standard deviation10.49105356
Coefficient of variation (CV)0.2023480838
Kurtosis0.7413570725
Mean51.84656737
Median Absolute Deviation (MAD)6
Skewness0.2899518895
Sum1035531.49
Variance110.0622048
MonotonicityNot monotonic
2021-11-29T11:31:10.546957image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
501044
 
5.2%
52923
 
4.6%
51864
 
4.3%
56776
 
3.9%
54775
 
3.9%
55767
 
3.8%
53767
 
3.8%
48759
 
3.8%
46695
 
3.5%
44645
 
3.2%
Other values (150)11958
59.8%
ValueCountFrequency (%)
2017
0.1%
20.53
 
< 0.1%
2115
0.1%
21.55
 
< 0.1%
2217
0.1%
2319
0.1%
23.52
 
< 0.1%
2431
0.2%
24.51
 
< 0.1%
2531
0.2%
ValueCountFrequency (%)
1091
 
< 0.1%
1051
 
< 0.1%
971
 
< 0.1%
962
< 0.1%
954
< 0.1%
942
< 0.1%
933
< 0.1%
92.51
 
< 0.1%
921
 
< 0.1%
91.51
 
< 0.1%

DBP-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct332
Distinct (%)1.7%
Missing27
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean88.14609273
Minimum32
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:10.644925image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum32
5-th percentile64
Q175.5
median85
Q397
95-th percentile120
Maximum300
Range268
Interquartile range (IQR)21.5

Descriptive statistics

Standard deviation20.65945875
Coefficient of variation (CV)0.2343774762
Kurtosis19.22165676
Mean88.14609273
Median Absolute Deviation (MAD)11
Skewness2.861997187
Sum1760541.91
Variance426.8132359
MonotonicityNot monotonic
2021-11-29T11:31:10.747206image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
80544
 
2.7%
84535
 
2.7%
82529
 
2.6%
76521
 
2.6%
78511
 
2.6%
86486
 
2.4%
81468
 
2.3%
79467
 
2.3%
88460
 
2.3%
90454
 
2.3%
Other values (322)14998
75.0%
ValueCountFrequency (%)
321
 
< 0.1%
362
 
< 0.1%
411
 
< 0.1%
41.51
 
< 0.1%
421
 
< 0.1%
453
< 0.1%
45.51
 
< 0.1%
467
< 0.1%
471
 
< 0.1%
47.51
 
< 0.1%
ValueCountFrequency (%)
3002
< 0.1%
2981
 
< 0.1%
2963
< 0.1%
2932
< 0.1%
2922
< 0.1%
2911
 
< 0.1%
2902
< 0.1%
2871
 
< 0.1%
2851
 
< 0.1%
2841
 
< 0.1%

Resp-min
Real number (ℝ≥0)

Distinct59
Distinct (%)0.3%
Missing43
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean13.07446009
Minimum1
Maximum35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:10.848771image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8
Q111
median13
Q315.5
95-th percentile18
Maximum35
Range34
Interquartile range (IQR)4.5

Descriptive statistics

Standard deviation3.497854282
Coefficient of variation (CV)0.2675333634
Kurtosis2.295771055
Mean13.07446009
Median Absolute Deviation (MAD)2
Skewness-0.4229964857
Sum260927
Variance12.23498458
MonotonicityNot monotonic
2021-11-29T11:31:10.946920image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
123400
17.0%
142642
13.2%
162519
12.6%
102141
10.7%
151641
8.2%
111408
7.0%
131387
6.9%
181036
 
5.2%
17614
 
3.1%
9487
 
2.4%
Other values (49)2682
13.4%
ValueCountFrequency (%)
1227
1.1%
1.518
 
0.1%
2140
0.7%
2.518
 
0.1%
359
 
0.3%
3.510
 
0.1%
444
 
0.2%
4.55
 
< 0.1%
553
 
0.3%
5.57
 
< 0.1%
ValueCountFrequency (%)
352
 
< 0.1%
342
 
< 0.1%
323
< 0.1%
312
 
< 0.1%
303
< 0.1%
293
< 0.1%
286
< 0.1%
27.51
 
< 0.1%
272
 
< 0.1%
26.51
 
< 0.1%

Resp-max
Real number (ℝ≥0)

Distinct137
Distinct (%)0.7%
Missing43
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean25.45011775
Minimum1
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:11.052195image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile18
Q122
median24
Q328
95-th percentile36
Maximum100
Range99
Interquartile range (IQR)6

Descriptive statistics

Standard deviation6.703606788
Coefficient of variation (CV)0.2634017985
Kurtosis28.77288584
Mean25.45011775
Median Absolute Deviation (MAD)3
Skewness3.409856074
Sum507908
Variance44.93834397
MonotonicityNot monotonic
2021-11-29T11:31:11.152373image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
242129
 
10.6%
221979
 
9.9%
201625
 
8.1%
261433
 
7.2%
251393
 
7.0%
281379
 
6.9%
181214
 
6.1%
231063
 
5.3%
30964
 
4.8%
21825
 
4.1%
Other values (127)5953
29.8%
ValueCountFrequency (%)
14
< 0.1%
1.51
 
< 0.1%
29
< 0.1%
36
< 0.1%
45
< 0.1%
4.51
 
< 0.1%
58
< 0.1%
65
< 0.1%
6.51
 
< 0.1%
73
 
< 0.1%
ValueCountFrequency (%)
1005
< 0.1%
997
< 0.1%
986
< 0.1%
975
< 0.1%
96.51
 
< 0.1%
964
< 0.1%
952
 
< 0.1%
943
< 0.1%
932
 
< 0.1%
921
 
< 0.1%

EtCO2-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct91
Distinct (%)2.8%
Missing16784
Missing (%)83.9%
Infinite0
Infinite (%)0.0%
Mean28.01912313
Minimum10
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:11.254482image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile12
Q122
median28
Q333
95-th percentile39.5
Maximum100
Range90
Interquartile range (IQR)11

Descriptive statistics

Standard deviation11.00698314
Coefficient of variation (CV)0.3928382442
Kurtosis16.56850982
Mean28.01912313
Median Absolute Deviation (MAD)5.5
Skewness2.812296261
Sum90109.5
Variance121.1536777
MonotonicityNot monotonic
2021-11-29T11:31:11.350200image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30155
 
0.8%
28145
 
0.7%
32130
 
0.7%
24128
 
0.6%
29128
 
0.6%
26123
 
0.6%
31121
 
0.6%
27113
 
0.6%
34111
 
0.6%
25109
 
0.5%
Other values (81)1953
 
9.8%
(Missing)16784
83.9%
ValueCountFrequency (%)
1075
0.4%
10.513
 
0.1%
1131
0.2%
11.58
 
< 0.1%
1242
0.2%
12.59
 
< 0.1%
1340
0.2%
13.510
 
0.1%
1431
0.2%
14.511
 
0.1%
ValueCountFrequency (%)
1007
< 0.1%
994
< 0.1%
986
< 0.1%
979
< 0.1%
963
 
< 0.1%
951
 
< 0.1%
942
 
< 0.1%
932
 
< 0.1%
924
< 0.1%
861
 
< 0.1%

EtCO2-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct124
Distinct (%)3.9%
Missing16784
Missing (%)83.9%
Infinite0
Infinite (%)0.0%
Mean38.2994403
Minimum10
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:11.452063image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile22
Q133
median38
Q343
95-th percentile52
Maximum100
Range90
Interquartile range (IQR)10

Descriptive statistics

Standard deviation11.25899176
Coefficient of variation (CV)0.2939727493
Kurtosis9.750683958
Mean38.2994403
Median Absolute Deviation (MAD)5
Skewness1.980621967
Sum123171
Variance126.7648955
MonotonicityNot monotonic
2021-11-29T11:31:11.547298image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
38149
 
0.7%
41147
 
0.7%
37140
 
0.7%
36139
 
0.7%
42137
 
0.7%
40135
 
0.7%
39135
 
0.7%
35130
 
0.7%
44111
 
0.6%
34106
 
0.5%
Other values (114)1887
 
9.4%
(Missing)16784
83.9%
ValueCountFrequency (%)
104
< 0.1%
10.55
< 0.1%
117
< 0.1%
126
< 0.1%
12.51
 
< 0.1%
134
< 0.1%
13.53
< 0.1%
145
< 0.1%
14.53
< 0.1%
154
< 0.1%
ValueCountFrequency (%)
10010
0.1%
994
 
< 0.1%
9810
0.1%
979
< 0.1%
963
 
< 0.1%
952
 
< 0.1%
942
 
< 0.1%
932
 
< 0.1%
924
 
< 0.1%
861
 
< 0.1%

BaseExcess-min
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct206
Distinct (%)36.9%
Missing19442
Missing (%)97.2%
Infinite0
Infinite (%)0.0%
Mean-3.851164875
Minimum-23.2
Maximum9.1
Zeros1
Zeros (%)< 0.1%
Negative467
Negative (%)2.3%
Memory size156.4 KiB
2021-11-29T11:31:11.730780image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-23.2
5-th percentile-11.1
Q1-5.975
median-3.7
Q3-1.3
95-th percentile3.015
Maximum9.1
Range32.3
Interquartile range (IQR)4.675

Descriptive statistics

Standard deviation4.310255972
Coefficient of variation (CV)-1.119208373
Kurtosis1.622403723
Mean-3.851164875
Median Absolute Deviation (MAD)2.4
Skewness-0.4472885894
Sum-2148.95
Variance18.57830654
MonotonicityNot monotonic
2021-11-29T11:31:11.823876image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-4.411
 
0.1%
-3.910
 
0.1%
-4.59
 
< 0.1%
-38
 
< 0.1%
-1.78
 
< 0.1%
-2.68
 
< 0.1%
-2.58
 
< 0.1%
-3.78
 
< 0.1%
-2.48
 
< 0.1%
-2.88
 
< 0.1%
Other values (196)472
 
2.4%
(Missing)19442
97.2%
ValueCountFrequency (%)
-23.21
< 0.1%
-21.21
< 0.1%
-18.251
< 0.1%
-17.41
< 0.1%
-16.61
< 0.1%
-161
< 0.1%
-15.81
< 0.1%
-15.11
< 0.1%
-151
< 0.1%
-14.81
< 0.1%
ValueCountFrequency (%)
9.11
< 0.1%
91
< 0.1%
7.951
< 0.1%
7.62
< 0.1%
6.81
< 0.1%
6.31
< 0.1%
5.71
< 0.1%
5.51
< 0.1%
5.41
< 0.1%
5.11
< 0.1%

BaseExcess-max
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct189
Distinct (%)33.9%
Missing19442
Missing (%)97.2%
Infinite0
Infinite (%)0.0%
Mean-1.143996416
Minimum-21.8
Maximum14.2
Zeros4
Zeros (%)< 0.1%
Negative333
Negative (%)1.7%
Memory size156.4 KiB
2021-11-29T11:31:11.922580image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-21.8
5-th percentile-8.0225
Q1-3.4
median-0.9
Q31.4
95-th percentile5.4
Maximum14.2
Range36
Interquartile range (IQR)4.8

Descriptive statistics

Standard deviation4.214126748
Coefficient of variation (CV)-3.683688769
Kurtosis2.166493674
Mean-1.143996416
Median Absolute Deviation (MAD)2.4
Skewness-0.4150854249
Sum-638.35
Variance17.75886425
MonotonicityNot monotonic
2021-11-29T11:31:12.018688image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.513
 
0.1%
-1.110
 
0.1%
-3.49
 
< 0.1%
-0.59
 
< 0.1%
-4.48
 
< 0.1%
1.58
 
< 0.1%
1.48
 
< 0.1%
-1.38
 
< 0.1%
-0.98
 
< 0.1%
-0.67
 
< 0.1%
Other values (179)470
 
2.4%
(Missing)19442
97.2%
ValueCountFrequency (%)
-21.81
< 0.1%
-18.251
< 0.1%
-15.651
< 0.1%
-15.11
< 0.1%
-14.351
< 0.1%
-13.851
< 0.1%
-12.61
< 0.1%
-11.81
< 0.1%
-11.41
< 0.1%
-11.32
< 0.1%
ValueCountFrequency (%)
14.21
 
< 0.1%
13.31
 
< 0.1%
11.11
 
< 0.1%
10.21
 
< 0.1%
9.11
 
< 0.1%
91
 
< 0.1%
8.51
 
< 0.1%
8.41
 
< 0.1%
7.91
 
< 0.1%
7.63
< 0.1%

HCO3-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct166
Distinct (%)39.9%
Missing19584
Missing (%)97.9%
Infinite0
Infinite (%)0.0%
Mean22.18509615
Minimum7.7
Maximum32.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:12.117815image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum7.7
5-th percentile16.9
Q120.4
median22.2
Q324.2125
95-th percentile27.9
Maximum32.4
Range24.7
Interquartile range (IQR)3.8125

Descriptive statistics

Standard deviation3.499780577
Coefficient of variation (CV)0.1577536808
Kurtosis1.392533606
Mean22.18509615
Median Absolute Deviation (MAD)2
Skewness-0.2309924944
Sum9229
Variance12.24846409
MonotonicityNot monotonic
2021-11-29T11:31:12.216318image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20.410
 
0.1%
229
 
< 0.1%
22.69
 
< 0.1%
24.89
 
< 0.1%
21.59
 
< 0.1%
23.58
 
< 0.1%
23.28
 
< 0.1%
21.38
 
< 0.1%
22.37
 
< 0.1%
20.77
 
< 0.1%
Other values (156)332
 
1.7%
(Missing)19584
97.9%
ValueCountFrequency (%)
7.71
< 0.1%
8.41
< 0.1%
12.451
< 0.1%
12.61
< 0.1%
13.11
< 0.1%
13.31
< 0.1%
13.61
< 0.1%
13.92
< 0.1%
14.12
< 0.1%
14.21
< 0.1%
ValueCountFrequency (%)
32.41
< 0.1%
322
< 0.1%
31.91
< 0.1%
30.91
< 0.1%
30.61
< 0.1%
30.11
< 0.1%
29.52
< 0.1%
29.42
< 0.1%
29.21
< 0.1%
29.12
< 0.1%

HCO3-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct145
Distinct (%)34.9%
Missing19584
Missing (%)97.9%
Infinite0
Infinite (%)0.0%
Mean24.56983173
Minimum7.7
Maximum36.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:12.312250image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum7.7
5-th percentile18.9
Q122.6
median24.85
Q326.4125
95-th percentile29.75
Maximum36.4
Range28.7
Interquartile range (IQR)3.8125

Descriptive statistics

Standard deviation3.360838926
Coefficient of variation (CV)0.1367872179
Kurtosis2.24279663
Mean24.56983173
Median Absolute Deviation (MAD)1.875
Skewness-0.3018458229
Sum10221.05
Variance11.29523828
MonotonicityNot monotonic
2021-11-29T11:31:12.406608image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25.313
 
0.1%
23.511
 
0.1%
24.510
 
0.1%
23.29
 
< 0.1%
25.99
 
< 0.1%
26.19
 
< 0.1%
269
 
< 0.1%
257
 
< 0.1%
24.67
 
< 0.1%
26.57
 
< 0.1%
Other values (135)325
 
1.6%
(Missing)19584
97.9%
ValueCountFrequency (%)
7.71
< 0.1%
13.11
< 0.1%
13.71
< 0.1%
151
< 0.1%
16.51
< 0.1%
16.81
< 0.1%
172
< 0.1%
17.31
< 0.1%
17.41
< 0.1%
17.51
< 0.1%
ValueCountFrequency (%)
36.41
< 0.1%
361
< 0.1%
35.31
< 0.1%
33.71
< 0.1%
32.91
< 0.1%
32.41
< 0.1%
322
< 0.1%
31.61
< 0.1%
31.11
< 0.1%
30.91
< 0.1%

FiO2-min
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
MISSING
SKEWED

Distinct67
Distinct (%)1.2%
Missing14178
Missing (%)70.9%
Infinite0
Infinite (%)0.0%
Mean0.4056853315
Minimum-50
Maximum2
Zeros0
Zeros (%)0.0%
Negative2
Negative (%)< 0.1%
Memory size156.4 KiB
2021-11-29T11:31:12.505643image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-50
5-th percentile0.21
Q10.3
median0.4
Q30.45
95-th percentile1
Maximum2
Range52
Interquartile range (IQR)0.15

Descriptive statistics

Standard deviation0.9536206482
Coefficient of variation (CV)2.350641185
Kurtosis2681.712423
Mean0.4056853315
Median Absolute Deviation (MAD)0.1
Skewness-50.73903075
Sum2361.9
Variance0.9093923408
MonotonicityNot monotonic
2021-11-29T11:31:12.605422image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.42241
 
11.2%
0.21719
 
3.6%
0.5693
 
3.5%
0.3378
 
1.9%
1328
 
1.6%
0.28294
 
1.5%
0.35202
 
1.0%
0.32156
 
0.8%
0.6145
 
0.7%
0.36119
 
0.6%
Other values (57)547
 
2.7%
(Missing)14178
70.9%
ValueCountFrequency (%)
-502
 
< 0.1%
0.011
 
< 0.1%
0.023
 
< 0.1%
0.031
 
< 0.1%
0.049
< 0.1%
0.059
< 0.1%
0.0613
0.1%
0.081
 
< 0.1%
0.11
 
< 0.1%
0.131
 
< 0.1%
ValueCountFrequency (%)
24
 
< 0.1%
1.21
 
< 0.1%
1328
1.6%
0.981
 
< 0.1%
0.953
 
< 0.1%
0.921
 
< 0.1%
0.910
 
0.1%
0.854
 
< 0.1%
0.841
 
< 0.1%
0.821
 
< 0.1%

FiO2-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
MISSING
SKEWED

Distinct68
Distinct (%)1.2%
Missing14178
Missing (%)70.9%
Infinite0
Infinite (%)0.0%
Mean1.261176572
Minimum0.04
Maximum4000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:12.705353image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.04
5-th percentile0.21
Q10.4
median0.5
Q30.8
95-th percentile1
Maximum4000
Range3999.96
Interquartile range (IQR)0.4

Descriptive statistics

Standard deviation52.41651778
Coefficient of variation (CV)41.56160125
Kurtosis5821.644562
Mean1.261176572
Median Absolute Deviation (MAD)0.2
Skewness76.2985385
Sum7342.57
Variance2747.491336
MonotonicityNot monotonic
2021-11-29T11:31:12.805845image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11330
 
6.7%
0.41168
 
5.8%
0.5915
 
4.6%
0.21585
 
2.9%
0.7329
 
1.6%
0.6286
 
1.4%
0.28230
 
1.1%
0.3162
 
0.8%
0.8150
 
0.8%
0.35116
 
0.6%
Other values (58)551
 
2.8%
(Missing)14178
70.9%
ValueCountFrequency (%)
0.042
 
< 0.1%
0.054
 
< 0.1%
0.064
 
< 0.1%
0.21585
2.9%
0.2413
 
0.1%
0.258
 
< 0.1%
0.262
 
< 0.1%
0.271
 
< 0.1%
0.28230
 
1.1%
0.291
 
< 0.1%
ValueCountFrequency (%)
40001
 
< 0.1%
5.051
 
< 0.1%
214
 
0.1%
1.71
 
< 0.1%
1.41
 
< 0.1%
1.31
 
< 0.1%
1.23
 
< 0.1%
11330
6.7%
0.981
 
< 0.1%
0.971
 
< 0.1%

pH-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct81
Distinct (%)1.4%
Missing14246
Missing (%)71.2%
Infinite0
Infinite (%)0.0%
Mean7.346866528
Minimum6.71
Maximum7.61
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:12.913086image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum6.71
5-th percentile7.2
Q17.3
median7.36
Q37.4
95-th percentile7.48
Maximum7.61
Range0.9
Interquartile range (IQR)0.1

Descriptive statistics

Standard deviation0.0906618608
Coefficient of variation (CV)0.01234020796
Kurtosis4.147079166
Mean7.346866528
Median Absolute Deviation (MAD)0.05
Skewness-1.128063207
Sum42273.87
Variance0.008219573004
MonotonicityNot monotonic
2021-11-29T11:31:13.008748image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.38350
 
1.8%
7.36343
 
1.7%
7.34321
 
1.6%
7.32304
 
1.5%
7.35277
 
1.4%
7.37277
 
1.4%
7.4276
 
1.4%
7.39256
 
1.3%
7.42242
 
1.2%
7.33238
 
1.2%
Other values (71)2870
 
14.3%
(Missing)14246
71.2%
ValueCountFrequency (%)
6.711
< 0.1%
6.721
< 0.1%
6.731
< 0.1%
6.781
< 0.1%
6.812
< 0.1%
6.821
< 0.1%
6.842
< 0.1%
6.851
< 0.1%
6.872
< 0.1%
6.882
< 0.1%
ValueCountFrequency (%)
7.612
 
< 0.1%
7.64
 
< 0.1%
7.593
 
< 0.1%
7.583
 
< 0.1%
7.574
 
< 0.1%
7.569
 
< 0.1%
7.556
 
< 0.1%
7.5420
0.1%
7.5312
0.1%
7.5225
0.1%

pH-max
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct63
Distinct (%)1.1%
Missing14246
Missing (%)71.2%
Infinite0
Infinite (%)0.0%
Mean7.407309698
Minimum6.81
Maximum7.71
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:13.109414image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum6.81
5-th percentile7.3
Q17.36
median7.41
Q37.45
95-th percentile7.52
Maximum7.71
Range0.9
Interquartile range (IQR)0.09

Descriptive statistics

Standard deviation0.07246876263
Coefficient of variation (CV)0.009783412006
Kurtosis2.21484331
Mean7.407309698
Median Absolute Deviation (MAD)0.05
Skewness-0.2612562861
Sum42621.66
Variance0.005251721557
MonotonicityNot monotonic
2021-11-29T11:31:13.290654image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.42371
 
1.9%
7.38368
 
1.8%
7.4364
 
1.8%
7.39316
 
1.6%
7.36309
 
1.5%
7.44300
 
1.5%
7.41293
 
1.5%
7.46275
 
1.4%
7.37269
 
1.3%
7.45266
 
1.3%
Other values (53)2623
 
13.1%
(Missing)14246
71.2%
ValueCountFrequency (%)
6.811
 
< 0.1%
6.851
 
< 0.1%
7.051
 
< 0.1%
7.061
 
< 0.1%
7.071
 
< 0.1%
7.091
 
< 0.1%
7.11
 
< 0.1%
7.111
 
< 0.1%
7.124
< 0.1%
7.142
< 0.1%
ValueCountFrequency (%)
7.711
 
< 0.1%
7.691
 
< 0.1%
7.681
 
< 0.1%
7.642
 
< 0.1%
7.634
 
< 0.1%
7.626
 
< 0.1%
7.6112
0.1%
7.612
0.1%
7.5920
0.1%
7.5822
0.1%

PaCO2-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct372
Distinct (%)6.4%
Missing14221
Missing (%)71.1%
Infinite0
Infinite (%)0.0%
Mean37.65852224
Minimum12
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:13.391607image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile26
Q132
median36.5
Q341.3
95-th percentile54
Maximum100
Range88
Interquartile range (IQR)9.3

Descriptive statistics

Standard deviation9.419204372
Coefficient of variation (CV)0.2501214549
Kurtosis5.640452899
Mean37.65852224
Median Absolute Deviation (MAD)4.5
Skewness1.638943563
Sum217628.6
Variance88.721411
MonotonicityNot monotonic
2021-11-29T11:31:13.487250image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34273
 
1.4%
36266
 
1.3%
38245
 
1.2%
35238
 
1.2%
32235
 
1.2%
37227
 
1.1%
40205
 
1.0%
33197
 
1.0%
39189
 
0.9%
31181
 
0.9%
Other values (362)3523
 
17.6%
(Missing)14221
71.1%
ValueCountFrequency (%)
121
 
< 0.1%
131
 
< 0.1%
157
< 0.1%
15.31
 
< 0.1%
165
< 0.1%
16.21
 
< 0.1%
16.42
 
< 0.1%
16.71
 
< 0.1%
1711
0.1%
189
< 0.1%
ValueCountFrequency (%)
1001
 
< 0.1%
951
 
< 0.1%
93.41
 
< 0.1%
931
 
< 0.1%
911
 
< 0.1%
892
< 0.1%
88.11
 
< 0.1%
881
 
< 0.1%
873
< 0.1%
861
 
< 0.1%

PaCO2-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct423
Distinct (%)7.3%
Missing14221
Missing (%)71.1%
Infinite0
Infinite (%)0.0%
Mean43.41301263
Minimum12
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:13.587539image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile29.5
Q136.8
median41.6
Q347
95-th percentile66.2
Maximum100
Range88
Interquartile range (IQR)10.2

Descriptive statistics

Standard deviation11.53500494
Coefficient of variation (CV)0.2657038579
Kurtosis4.826518059
Mean43.41301263
Median Absolute Deviation (MAD)5.4
Skewness1.741863092
Sum250883.8
Variance133.0563389
MonotonicityNot monotonic
2021-11-29T11:31:13.682684image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
40256
 
1.3%
42252
 
1.3%
38227
 
1.1%
36212
 
1.1%
44204
 
1.0%
39189
 
0.9%
41186
 
0.9%
43186
 
0.9%
34177
 
0.9%
46176
 
0.9%
Other values (413)3714
 
18.6%
(Missing)14221
71.1%
ValueCountFrequency (%)
121
 
< 0.1%
153
< 0.1%
15.31
 
< 0.1%
162
< 0.1%
16.71
 
< 0.1%
173
< 0.1%
184
< 0.1%
18.81
 
< 0.1%
193
< 0.1%
19.21
 
< 0.1%
ValueCountFrequency (%)
1006
< 0.1%
994
< 0.1%
986
< 0.1%
975
< 0.1%
962
 
< 0.1%
952
 
< 0.1%
944
< 0.1%
93.41
 
< 0.1%
934
< 0.1%
92.51
 
< 0.1%

SaO2-min
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct298
Distinct (%)5.8%
Missing14875
Missing (%)74.4%
Infinite0
Infinite (%)0.0%
Mean95.48681951
Minimum23
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:13.782299image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum23
5-th percentile88
Q194.4
median96.7
Q398.3
95-th percentile99.4
Maximum100
Range77
Interquartile range (IQR)3.9

Descriptive statistics

Standard deviation4.919157181
Coefficient of variation (CV)0.05151660937
Kurtosis36.07666916
Mean95.48681951
Median Absolute Deviation (MAD)1.8
Skewness-4.524774396
Sum489369.95
Variance24.19810737
MonotonicityNot monotonic
2021-11-29T11:31:13.882216image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
98.8120
 
0.6%
99113
 
0.6%
98.6102
 
0.5%
98.798
 
0.5%
98.298
 
0.5%
9795
 
0.5%
99.294
 
0.5%
97.692
 
0.5%
98.492
 
0.5%
97.888
 
0.4%
Other values (288)4133
 
20.7%
(Missing)14875
74.4%
ValueCountFrequency (%)
231
< 0.1%
29.11
< 0.1%
36.61
< 0.1%
45.21
< 0.1%
50.31
< 0.1%
52.51
< 0.1%
54.71
< 0.1%
56.61
< 0.1%
58.21
< 0.1%
58.31
< 0.1%
ValueCountFrequency (%)
1001
 
< 0.1%
99.930
0.1%
99.838
0.2%
99.748
0.2%
99.654
0.3%
99.552
 
< 0.1%
99.564
0.3%
99.452
 
< 0.1%
99.471
0.4%
99.358
0.3%

SaO2-max
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct187
Distinct (%)3.6%
Missing14875
Missing (%)74.4%
Infinite0
Infinite (%)0.0%
Mean97.51632195
Minimum50.3
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:13.985995image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum50.3
5-th percentile93.1
Q196.8
median98.3
Q399.2
95-th percentile99.7
Maximum100
Range49.7
Interquartile range (IQR)2.4

Descriptive statistics

Standard deviation2.842030854
Coefficient of variation (CV)0.02914415554
Kurtosis54.10734636
Mean97.51632195
Median Absolute Deviation (MAD)1
Skewness-5.276013539
Sum499771.15
Variance8.077139377
MonotonicityNot monotonic
2021-11-29T11:31:14.087560image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99.4203
 
1.0%
99.2196
 
1.0%
99.5185
 
0.9%
99.6180
 
0.9%
99174
 
0.9%
98.8165
 
0.8%
98.9161
 
0.8%
99.7160
 
0.8%
98.6156
 
0.8%
99.3155
 
0.8%
Other values (177)3390
 
17.0%
(Missing)14875
74.4%
ValueCountFrequency (%)
50.31
< 0.1%
52.51
< 0.1%
58.81
< 0.1%
65.11
< 0.1%
65.61
< 0.1%
681
< 0.1%
68.21
< 0.1%
70.81
< 0.1%
72.61
< 0.1%
73.31
< 0.1%
ValueCountFrequency (%)
1007
 
< 0.1%
99.972
 
0.4%
99.851
 
< 0.1%
99.8132
0.7%
99.753
 
< 0.1%
99.7160
0.8%
99.6180
0.9%
99.552
 
< 0.1%
99.5185
0.9%
99.451
 
< 0.1%

AST-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct542
Distinct (%)6.4%
Missing11536
Missing (%)57.7%
Infinite0
Infinite (%)0.0%
Mean74.53308129
Minimum5
Maximum8567
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:14.189654image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile12
Q118
median27
Q348
95-th percentile216.85
Maximum8567
Range8562
Interquartile range (IQR)30

Descriptive statistics

Standard deviation280.7648406
Coefficient of variation (CV)3.766982871
Kurtosis310.0415639
Mean74.53308129
Median Absolute Deviation (MAD)11
Skewness15.09768056
Sum630848
Variance78828.89569
MonotonicityNot monotonic
2021-11-29T11:31:14.286479image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17324
 
1.6%
20307
 
1.5%
16306
 
1.5%
19306
 
1.5%
18304
 
1.5%
21293
 
1.5%
15270
 
1.4%
22267
 
1.3%
14259
 
1.3%
24251
 
1.3%
Other values (532)5577
27.9%
(Missing)11536
57.7%
ValueCountFrequency (%)
59
 
< 0.1%
68
 
< 0.1%
79
 
< 0.1%
825
 
0.1%
943
 
0.2%
1080
 
0.4%
11126
0.6%
12175
0.9%
13187
0.9%
14259
1.3%
ValueCountFrequency (%)
85671
< 0.1%
79061
< 0.1%
65601
< 0.1%
56941
< 0.1%
51551
< 0.1%
50121
< 0.1%
48971
< 0.1%
45061
< 0.1%
44331
< 0.1%
43401
< 0.1%

AST-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct717
Distinct (%)8.5%
Missing11536
Missing (%)57.7%
Infinite0
Infinite (%)0.0%
Mean137.2675449
Minimum5
Maximum9961
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:14.391224image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile13
Q120
median29
Q356
95-th percentile364.85
Maximum9961
Range9956
Interquartile range (IQR)36

Descriptive statistics

Standard deviation621.3371001
Coefficient of variation (CV)4.526467641
Kurtosis120.1149451
Mean137.2675449
Median Absolute Deviation (MAD)12
Skewness10.16229717
Sum1161832.5
Variance386059.792
MonotonicityNot monotonic
2021-11-29T11:31:14.494092image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17292
 
1.5%
21289
 
1.4%
20286
 
1.4%
18283
 
1.4%
19281
 
1.4%
22269
 
1.3%
16256
 
1.3%
23242
 
1.2%
24236
 
1.2%
15220
 
1.1%
Other values (707)5810
29.0%
(Missing)11536
57.7%
ValueCountFrequency (%)
52
 
< 0.1%
65
 
< 0.1%
79
 
< 0.1%
814
 
0.1%
935
 
0.2%
9.51
 
< 0.1%
1060
0.3%
11106
0.5%
12143
0.7%
13142
0.7%
ValueCountFrequency (%)
99611
< 0.1%
97471
< 0.1%
97101
< 0.1%
96021
< 0.1%
95821
< 0.1%
95201
< 0.1%
94891
< 0.1%
92441
< 0.1%
92291
< 0.1%
91851
< 0.1%

BUN-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct167
Distinct (%)0.9%
Missing1591
Missing (%)8.0%
Infinite0
Infinite (%)0.0%
Mean19.24591233
Minimum1
Maximum177
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:14.596760image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q110
median15
Q322
95-th percentile51
Maximum177
Range176
Interquartile range (IQR)12

Descriptive statistics

Standard deviation16.02085159
Coefficient of variation (CV)0.8324287939
Kurtosis11.64271136
Mean19.24591233
Median Absolute Deviation (MAD)6
Skewness2.836883334
Sum354298
Variance256.6676855
MonotonicityNot monotonic
2021-11-29T11:31:14.695636image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
121068
 
5.3%
131066
 
5.3%
111040
 
5.2%
10991
 
5.0%
9909
 
4.5%
14892
 
4.5%
8860
 
4.3%
15844
 
4.2%
16755
 
3.8%
17731
 
3.7%
Other values (157)9253
46.3%
(Missing)1591
 
8.0%
ValueCountFrequency (%)
147
 
0.2%
274
 
0.4%
3183
 
0.9%
3.51
 
< 0.1%
4307
1.5%
4.52
 
< 0.1%
5438
2.2%
5.52
 
< 0.1%
6571
2.9%
7719
3.6%
ValueCountFrequency (%)
1771
< 0.1%
1731
< 0.1%
1701
< 0.1%
1611
< 0.1%
1571
< 0.1%
1521
< 0.1%
1511
< 0.1%
1491
< 0.1%
1451
< 0.1%
1421
< 0.1%

BUN-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct208
Distinct (%)1.1%
Missing1591
Missing (%)8.0%
Infinite0
Infinite (%)0.0%
Mean23.73311967
Minimum1
Maximum268
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:14.884365image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7
Q112
median17
Q328
95-th percentile64
Maximum268
Range267
Interquartile range (IQR)16

Descriptive statistics

Standard deviation20.10751106
Coefficient of variation (CV)0.8472342171
Kurtosis12.91482916
Mean23.73311967
Median Absolute Deviation (MAD)7
Skewness2.88575184
Sum436903
Variance404.3120011
MonotonicityNot monotonic
2021-11-29T11:31:14.983588image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14925
 
4.6%
13911
 
4.6%
12880
 
4.4%
15877
 
4.4%
11851
 
4.3%
10787
 
3.9%
17765
 
3.8%
16750
 
3.8%
18680
 
3.4%
9660
 
3.3%
Other values (198)10323
51.6%
(Missing)1591
 
8.0%
ValueCountFrequency (%)
16
 
< 0.1%
221
 
0.1%
369
 
0.3%
4138
 
0.7%
4.52
 
< 0.1%
5236
1.2%
5.52
 
< 0.1%
6372
1.9%
6.51
 
< 0.1%
7477
2.4%
ValueCountFrequency (%)
2681
< 0.1%
2521
< 0.1%
2321
< 0.1%
2271
< 0.1%
2111
< 0.1%
2021
< 0.1%
2011
< 0.1%
1901
< 0.1%
1891
< 0.1%
1862
< 0.1%

Alkalinephos-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct422
Distinct (%)5.0%
Missing11530
Missing (%)57.6%
Infinite0
Infinite (%)0.0%
Mean85.2688902
Minimum11
Maximum1650
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:15.082350image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile32.45
Q151
median67
Q394
95-th percentile189
Maximum1650
Range1639
Interquartile range (IQR)43

Descriptive statistics

Standard deviation77.18846698
Coefficient of variation (CV)0.9052359753
Kurtosis80.63166588
Mean85.2688902
Median Absolute Deviation (MAD)19
Skewness6.819773184
Sum722227.5
Variance5958.059435
MonotonicityNot monotonic
2021-11-29T11:31:15.180302image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
56150
 
0.8%
58146
 
0.7%
52140
 
0.7%
54139
 
0.7%
51139
 
0.7%
53136
 
0.7%
49135
 
0.7%
61134
 
0.7%
57134
 
0.7%
46132
 
0.7%
Other values (412)7085
35.4%
(Missing)11530
57.6%
ValueCountFrequency (%)
112
 
< 0.1%
121
 
< 0.1%
132
 
< 0.1%
142
 
< 0.1%
155
< 0.1%
167
< 0.1%
177
< 0.1%
186
< 0.1%
1910
0.1%
209
< 0.1%
ValueCountFrequency (%)
16502
< 0.1%
12141
< 0.1%
11601
< 0.1%
11291
< 0.1%
10721
< 0.1%
9871
< 0.1%
9721
< 0.1%
9581
< 0.1%
9351
< 0.1%
9281
< 0.1%

Alkalinephos-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct458
Distinct (%)5.4%
Missing11530
Missing (%)57.6%
Infinite0
Infinite (%)0.0%
Mean91.7742621
Minimum11
Maximum1650
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:15.283939image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile36
Q153
median70
Q3100
95-th percentile209
Maximum1650
Range1639
Interquartile range (IQR)47

Descriptive statistics

Standard deviation86.9212757
Coefficient of variation (CV)0.9471203986
Kurtosis71.98889947
Mean91.7742621
Median Absolute Deviation (MAD)20
Skewness6.678583052
Sum777328
Variance7555.30817
MonotonicityNot monotonic
2021-11-29T11:31:15.382270image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
53140
 
0.7%
66139
 
0.7%
57134
 
0.7%
58133
 
0.7%
55133
 
0.7%
56132
 
0.7%
54131
 
0.7%
69126
 
0.6%
63125
 
0.6%
61124
 
0.6%
Other values (448)7153
35.8%
(Missing)11530
57.6%
ValueCountFrequency (%)
112
 
< 0.1%
131
 
< 0.1%
141
 
< 0.1%
151
 
< 0.1%
162
 
< 0.1%
184
< 0.1%
194
< 0.1%
203
 
< 0.1%
217
< 0.1%
228
< 0.1%
ValueCountFrequency (%)
16502
< 0.1%
14471
< 0.1%
13661
< 0.1%
12761
< 0.1%
12141
< 0.1%
11341
< 0.1%
11291
< 0.1%
11161
< 0.1%
10721
< 0.1%
10051
< 0.1%

Calcium-min
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct327
Distinct (%)1.8%
Missing1550
Missing (%)7.8%
Infinite0
Infinite (%)0.0%
Mean6.739645528
Minimum1
Maximum27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:15.485471image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.09
Q16.8
median8.1
Q38.6
95-th percentile9.3
Maximum27
Range26
Interquartile range (IQR)1.8

Descriptive statistics

Standard deviation3.067395095
Coefficient of variation (CV)0.455127066
Kurtosis0.02832909665
Mean6.739645528
Median Absolute Deviation (MAD)0.7
Skewness-1.024280748
Sum124346.46
Variance9.408912672
MonotonicityNot monotonic
2021-11-29T11:31:15.582946image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.3938
 
4.7%
8.5921
 
4.6%
8.2896
 
4.5%
8.6886
 
4.4%
8.4885
 
4.4%
8.1811
 
4.1%
8.8770
 
3.9%
8.7768
 
3.8%
8725
 
3.6%
8.9666
 
3.3%
Other values (317)10184
50.9%
(Missing)1550
 
7.8%
ValueCountFrequency (%)
152
 
0.3%
1.0155
 
0.3%
1.0274
0.4%
1.0371
0.4%
1.0493
0.5%
1.0578
0.4%
1.06113
0.6%
1.07108
0.5%
1.08155
0.8%
1.09169
0.8%
ValueCountFrequency (%)
271
 
< 0.1%
25.21
 
< 0.1%
23.71
 
< 0.1%
191
 
< 0.1%
18.82
 
< 0.1%
18.63
< 0.1%
18.24
< 0.1%
182
 
< 0.1%
17.85
< 0.1%
17.61
 
< 0.1%

Calcium-max
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct241
Distinct (%)1.3%
Missing1550
Missing (%)7.8%
Infinite0
Infinite (%)0.0%
Mean8.680187534
Minimum1.07
Maximum27.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:15.678051image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1.07
5-th percentile7.5
Q18.2
median8.6
Q39
95-th percentile9.7775
Maximum27.9
Range26.83
Interquartile range (IQR)0.8

Descriptive statistics

Standard deviation1.253103093
Coefficient of variation (CV)0.1443635968
Kurtosis41.41546674
Mean8.680187534
Median Absolute Deviation (MAD)0.4
Skewness4.233694042
Sum160149.46
Variance1.570267361
MonotonicityNot monotonic
2021-11-29T11:31:15.779367image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.51208
 
6.0%
8.61196
 
6.0%
8.71149
 
5.7%
8.31144
 
5.7%
8.81110
 
5.5%
8.41086
 
5.4%
8.91056
 
5.3%
8.2954
 
4.8%
9944
 
4.7%
8.1867
 
4.3%
Other values (231)7736
38.7%
(Missing)1550
 
7.8%
ValueCountFrequency (%)
1.072
< 0.1%
1.083
< 0.1%
1.091
 
< 0.1%
1.12
< 0.1%
1.112
< 0.1%
1.121
 
< 0.1%
1.132
< 0.1%
1.141
 
< 0.1%
1.161
 
< 0.1%
1.172
< 0.1%
ValueCountFrequency (%)
27.91
< 0.1%
271
< 0.1%
25.21
< 0.1%
24.91
< 0.1%
23.71
< 0.1%
22.61
< 0.1%
22.22
< 0.1%
21.21
< 0.1%
20.61
< 0.1%
20.42
< 0.1%

Chloride-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct56
Distinct (%)3.5%
Missing18383
Missing (%)91.9%
Infinite0
Infinite (%)0.0%
Mean104.9931973
Minimum74
Maximum124
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:15.876901image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum74
5-th percentile96
Q1103
median105
Q3108
95-th percentile112
Maximum124
Range50
Interquartile range (IQR)5

Descriptive statistics

Standard deviation5.120541116
Coefficient of variation (CV)0.04877021796
Kurtosis3.206393389
Mean104.9931973
Median Absolute Deviation (MAD)3
Skewness-0.8108677937
Sum169774
Variance26.21994132
MonotonicityNot monotonic
2021-11-29T11:31:15.975825image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
105161
 
0.8%
107160
 
0.8%
106155
 
0.8%
108148
 
0.7%
104127
 
0.6%
103118
 
0.6%
10998
 
0.5%
10294
 
0.5%
11079
 
0.4%
10156
 
0.3%
Other values (46)421
 
2.1%
(Missing)18383
91.9%
ValueCountFrequency (%)
741
 
< 0.1%
781
 
< 0.1%
801
 
< 0.1%
821
 
< 0.1%
832
 
< 0.1%
851
 
< 0.1%
863
< 0.1%
885
< 0.1%
893
< 0.1%
903
< 0.1%
ValueCountFrequency (%)
1243
 
< 0.1%
1231
 
< 0.1%
1221
 
< 0.1%
1201
 
< 0.1%
1193
 
< 0.1%
1184
 
< 0.1%
1177
< 0.1%
1161
 
< 0.1%
1157
< 0.1%
11415
0.1%

Chloride-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct53
Distinct (%)3.3%
Missing18383
Missing (%)91.9%
Infinite0
Infinite (%)0.0%
Mean106.7959184
Minimum74
Maximum124
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:16.073997image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum74
5-th percentile97
Q1104
median107
Q3110
95-th percentile115
Maximum124
Range50
Interquartile range (IQR)6

Descriptive statistics

Standard deviation5.408307065
Coefficient of variation (CV)0.05064151465
Kurtosis2.309776643
Mean106.7959184
Median Absolute Deviation (MAD)3
Skewness-0.5865828136
Sum172689
Variance29.24978531
MonotonicityNot monotonic
2021-11-29T11:31:16.173338image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
107157
 
0.8%
108147
 
0.7%
109135
 
0.7%
106134
 
0.7%
105116
 
0.6%
110112
 
0.6%
10495
 
0.5%
11194
 
0.5%
10387
 
0.4%
10262
 
0.3%
Other values (43)478
 
2.4%
(Missing)18383
91.9%
ValueCountFrequency (%)
741
 
< 0.1%
821
 
< 0.1%
851
 
< 0.1%
863
 
< 0.1%
884
< 0.1%
892
 
< 0.1%
904
< 0.1%
915
< 0.1%
924
< 0.1%
938
< 0.1%
ValueCountFrequency (%)
1247
< 0.1%
1231
 
< 0.1%
1222
 
< 0.1%
1213
 
< 0.1%
1206
 
< 0.1%
1195
 
< 0.1%
1189
< 0.1%
1178
< 0.1%
116.51
 
< 0.1%
11617
0.1%

Creatinine-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct1018
Distinct (%)5.5%
Missing1588
Missing (%)7.9%
Infinite0
Infinite (%)0.0%
Mean1.445464371
Minimum0.2
Maximum25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:16.271331image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.2
5-th percentile0.49
Q10.69
median0.89
Q31.26
95-th percentile5.02
Maximum25
Range24.8
Interquartile range (IQR)0.57

Descriptive statistics

Standard deviation1.902371228
Coefficient of variation (CV)1.316096935
Kurtosis28.92521167
Mean1.445464371
Median Absolute Deviation (MAD)0.24
Skewness4.707814211
Sum26613.89
Variance3.619016291
MonotonicityNot monotonic
2021-11-29T11:31:16.453545image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.8281
 
1.4%
0.81279
 
1.4%
0.79275
 
1.4%
0.82263
 
1.3%
0.77259
 
1.3%
0.69258
 
1.3%
0.73254
 
1.3%
0.68244
 
1.2%
0.78242
 
1.2%
0.72241
 
1.2%
Other values (1008)15816
79.1%
(Missing)1588
 
7.9%
ValueCountFrequency (%)
0.24
 
< 0.1%
0.211
 
< 0.1%
0.222
 
< 0.1%
0.231
 
< 0.1%
0.241
 
< 0.1%
0.251
 
< 0.1%
0.272
 
< 0.1%
0.285
 
< 0.1%
0.293
 
< 0.1%
0.376
0.4%
ValueCountFrequency (%)
251
< 0.1%
23.831
< 0.1%
23.711
< 0.1%
23.651
< 0.1%
22.961
< 0.1%
22.011
< 0.1%
21.971
< 0.1%
21.461
< 0.1%
21.311
< 0.1%
21.181
< 0.1%

Creatinine-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct1177
Distinct (%)6.4%
Missing1588
Missing (%)7.9%
Infinite0
Infinite (%)0.0%
Mean1.714813165
Minimum0.2
Maximum41.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:16.553253image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.2
5-th percentile0.55
Q10.77
median1
Q31.46
95-th percentile6.3945
Maximum41.9
Range41.7
Interquartile range (IQR)0.69

Descriptive statistics

Standard deviation2.338576173
Coefficient of variation (CV)1.363749836
Kurtosis27.40770534
Mean1.714813165
Median Absolute Deviation (MAD)0.28
Skewness4.488848926
Sum31573.14
Variance5.468938518
MonotonicityNot monotonic
2021-11-29T11:31:16.645842image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.81261
 
1.3%
0.8241
 
1.2%
0.84240
 
1.2%
0.82238
 
1.2%
0.78226
 
1.1%
0.89224
 
1.1%
0.76219
 
1.1%
0.79219
 
1.1%
0.77219
 
1.1%
0.73217
 
1.1%
Other values (1167)16108
80.5%
(Missing)1588
 
7.9%
ValueCountFrequency (%)
0.21
 
< 0.1%
0.221
 
< 0.1%
0.241
 
< 0.1%
0.261
 
< 0.1%
0.272
 
< 0.1%
0.281
 
< 0.1%
0.291
 
< 0.1%
0.331
0.2%
0.315
 
< 0.1%
0.325
 
< 0.1%
ValueCountFrequency (%)
41.91
 
< 0.1%
29.861
 
< 0.1%
29.21
 
< 0.1%
254
< 0.1%
24.991
 
< 0.1%
24.031
 
< 0.1%
241
 
< 0.1%
23.831
 
< 0.1%
22.351
 
< 0.1%
22.21
 
< 0.1%

Bilirubin_direct-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct158
Distinct (%)10.7%
Missing18529
Missing (%)92.6%
Infinite0
Infinite (%)0.0%
Mean0.6810605031
Minimum0.01
Maximum20.57
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:16.745156image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.1
Q10.1
median0.2
Q30.4
95-th percentile2.35
Maximum20.57
Range20.56
Interquartile range (IQR)0.3

Descriptive statistics

Standard deviation1.918581063
Coefficient of variation (CV)2.817049373
Kurtosis58.88859506
Mean0.6810605031
Median Absolute Deviation (MAD)0.1
Skewness7.117946386
Sum1001.84
Variance3.680953296
MonotonicityNot monotonic
2021-11-29T11:31:16.837603image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1449
 
2.2%
0.2275
 
1.4%
0.3125
 
0.6%
0.487
 
0.4%
0.540
 
0.2%
0.633
 
0.2%
123
 
0.1%
0.721
 
0.1%
1.114
 
0.1%
1.213
 
0.1%
Other values (148)391
 
2.0%
(Missing)18529
92.6%
ValueCountFrequency (%)
0.017
 
< 0.1%
0.024
 
< 0.1%
0.035
 
< 0.1%
0.044
 
< 0.1%
0.056
 
< 0.1%
0.066
 
< 0.1%
0.077
 
< 0.1%
0.084
 
< 0.1%
0.0911
 
0.1%
0.1449
2.2%
ValueCountFrequency (%)
20.571
< 0.1%
202
< 0.1%
19.541
< 0.1%
19.081
< 0.1%
19.051
< 0.1%
18.181
< 0.1%
17.41
< 0.1%
16.61
< 0.1%
15.61
< 0.1%
151
< 0.1%

Bilirubin_direct-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct170
Distinct (%)11.6%
Missing18529
Missing (%)92.6%
Infinite0
Infinite (%)0.0%
Mean0.7670700204
Minimum0.01
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:16.933315image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.1
Q10.1
median0.2
Q30.47
95-th percentile2.705
Maximum30
Range29.99
Interquartile range (IQR)0.37

Descriptive statistics

Standard deviation2.200593963
Coefficient of variation (CV)2.868830621
Kurtosis61.76617545
Mean0.7670700204
Median Absolute Deviation (MAD)0.1
Skewness7.136593048
Sum1128.36
Variance4.84261379
MonotonicityNot monotonic
2021-11-29T11:31:17.028321image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1429
 
2.1%
0.2275
 
1.4%
0.3128
 
0.6%
0.484
 
0.4%
0.538
 
0.2%
0.633
 
0.2%
120
 
0.1%
0.718
 
0.1%
0.816
 
0.1%
1.114
 
0.1%
Other values (160)416
 
2.1%
(Missing)18529
92.6%
ValueCountFrequency (%)
0.015
 
< 0.1%
0.024
 
< 0.1%
0.035
 
< 0.1%
0.044
 
< 0.1%
0.054
 
< 0.1%
0.066
 
< 0.1%
0.077
 
< 0.1%
0.084
 
< 0.1%
0.0910
 
0.1%
0.1429
2.1%
ValueCountFrequency (%)
301
< 0.1%
23.621
< 0.1%
20.571
< 0.1%
20.551
< 0.1%
202
< 0.1%
19.31
< 0.1%
18.611
< 0.1%
18.51
< 0.1%
16.61
< 0.1%
15.61
< 0.1%

Glucose-min
Real number (ℝ≥0)

MISSING

Distinct394
Distinct (%)2.1%
Missing1173
Missing (%)5.9%
Infinite0
Infinite (%)0.0%
Mean101.9483587
Minimum13
Maximum409
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:17.130200image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum13
5-th percentile66
Q186
median98
Q3114
95-th percentile151
Maximum409
Range396
Interquartile range (IQR)28

Descriptive statistics

Standard deviation27.98982318
Coefficient of variation (CV)0.2745490318
Kurtosis8.007447523
Mean101.9483587
Median Absolute Deviation (MAD)14
Skewness1.705717808
Sum1919381.75
Variance783.4302018
MonotonicityNot monotonic
2021-11-29T11:31:17.230640image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
96405
 
2.0%
95401
 
2.0%
97397
 
2.0%
93391
 
2.0%
90387
 
1.9%
99382
 
1.9%
94380
 
1.9%
91379
 
1.9%
92371
 
1.9%
101371
 
1.9%
Other values (384)14963
74.8%
(Missing)1173
 
5.9%
ValueCountFrequency (%)
131
 
< 0.1%
151
 
< 0.1%
161
 
< 0.1%
211
 
< 0.1%
23.51
 
< 0.1%
261
 
< 0.1%
282
 
< 0.1%
29.51
 
< 0.1%
3023
0.1%
30.51
 
< 0.1%
ValueCountFrequency (%)
4091
< 0.1%
3891
< 0.1%
369.51
< 0.1%
3671
< 0.1%
3541
< 0.1%
349.51
< 0.1%
3231
< 0.1%
3221
< 0.1%
3001
< 0.1%
2971
< 0.1%

Glucose-max
Real number (ℝ≥0)

MISSING

Distinct744
Distinct (%)4.0%
Missing1173
Missing (%)5.9%
Infinite0
Infinite (%)0.0%
Mean170.4204116
Minimum44
Maximum891
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:17.335561image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum44
5-th percentile94
Q1122
median152
Q3195
95-th percentile313
Maximum891
Range847
Interquartile range (IQR)73

Descriptive statistics

Standard deviation72.78074433
Coefficient of variation (CV)0.4270658874
Kurtosis7.229435721
Mean170.4204116
Median Absolute Deviation (MAD)34
Skewness2.086764832
Sum3208505.09
Variance5297.036745
MonotonicityNot monotonic
2021-11-29T11:31:17.425890image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
147176
 
0.9%
146171
 
0.9%
136169
 
0.8%
133169
 
0.8%
121168
 
0.8%
150164
 
0.8%
115164
 
0.8%
120161
 
0.8%
140160
 
0.8%
134158
 
0.8%
Other values (734)17167
85.8%
(Missing)1173
 
5.9%
ValueCountFrequency (%)
441
 
< 0.1%
511
 
< 0.1%
59.51
 
< 0.1%
611
 
< 0.1%
621
 
< 0.1%
631
 
< 0.1%
663
< 0.1%
671
 
< 0.1%
682
< 0.1%
691
 
< 0.1%
ValueCountFrequency (%)
8911
< 0.1%
8711
< 0.1%
8501
< 0.1%
7881
< 0.1%
7571
< 0.1%
7341
< 0.1%
7221
< 0.1%
7081
< 0.1%
6931
< 0.1%
6921
< 0.1%

Lactate-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct493
Distinct (%)10.4%
Missing15240
Missing (%)76.2%
Infinite0
Infinite (%)0.0%
Mean1.765405462
Minimum0.4
Maximum19.12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:17.522726image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.4
5-th percentile0.7495
Q11.07
median1.41
Q31.98
95-th percentile3.7605
Maximum19.12
Range18.72
Interquartile range (IQR)0.91

Descriptive statistics

Standard deviation1.383693755
Coefficient of variation (CV)0.7837824143
Kurtosis38.8292031
Mean1.765405462
Median Absolute Deviation (MAD)0.41
Skewness5.058561021
Sum8403.33
Variance1.914608409
MonotonicityNot monotonic
2021-11-29T11:31:17.623022image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.269
 
0.3%
0.863
 
0.3%
161
 
0.3%
1.161
 
0.3%
0.953
 
0.3%
1.2349
 
0.2%
1.348
 
0.2%
0.747
 
0.2%
1.3144
 
0.2%
1.443
 
0.2%
Other values (483)4222
 
21.1%
(Missing)15240
76.2%
ValueCountFrequency (%)
0.41
 
< 0.1%
0.461
 
< 0.1%
0.511
0.1%
0.533
 
< 0.1%
0.542
 
< 0.1%
0.552
 
< 0.1%
0.564
 
< 0.1%
0.574
 
< 0.1%
0.581
 
< 0.1%
0.592
 
< 0.1%
ValueCountFrequency (%)
19.121
< 0.1%
17.752
< 0.1%
17.421
< 0.1%
16.151
< 0.1%
15.941
< 0.1%
151
< 0.1%
14.441
< 0.1%
13.671
< 0.1%
13.061
< 0.1%
12.981
< 0.1%

Lactate-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct874
Distinct (%)18.4%
Missing15240
Missing (%)76.2%
Infinite0
Infinite (%)0.0%
Mean2.890462185
Minimum0.5
Maximum22.25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:17.730529image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.5
5-th percentile0.88
Q11.34
median1.95
Q33.34
95-th percentile8.201
Maximum22.25
Range21.75
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.675611187
Coefficient of variation (CV)0.9256689818
Kurtosis10.73650928
Mean2.890462185
Median Absolute Deviation (MAD)0.75
Skewness2.871853144
Sum13758.6
Variance7.158895227
MonotonicityNot monotonic
2021-11-29T11:31:17.821831image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.437
 
0.2%
1.237
 
0.2%
1.337
 
0.2%
1.135
 
0.2%
1.733
 
0.2%
1.3430
 
0.1%
1.3530
 
0.1%
0.929
 
0.1%
129
 
0.1%
1.4728
 
0.1%
Other values (864)4435
 
22.2%
(Missing)15240
76.2%
ValueCountFrequency (%)
0.54
< 0.1%
0.541
 
< 0.1%
0.551
 
< 0.1%
0.562
 
< 0.1%
0.574
< 0.1%
0.591
 
< 0.1%
0.66
< 0.1%
0.611
 
< 0.1%
0.621
 
< 0.1%
0.634
< 0.1%
ValueCountFrequency (%)
22.251
< 0.1%
21.521
< 0.1%
21.261
< 0.1%
21.211
< 0.1%
19.791
< 0.1%
19.711
< 0.1%
19.661
< 0.1%
19.321
< 0.1%
19.121
< 0.1%
19.021
< 0.1%

Magnesium-min
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct58
Distinct (%)0.4%
Missing3543
Missing (%)17.7%
Infinite0
Infinite (%)0.0%
Mean1.904144133
Minimum0.5
Maximum6.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:18.000336image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.5
5-th percentile1.4
Q11.7
median1.9
Q32.1
95-th percentile2.4
Maximum6.2
Range5.7
Interquartile range (IQR)0.4

Descriptive statistics

Standard deviation0.3193901207
Coefficient of variation (CV)0.1677342146
Kurtosis9.487936571
Mean1.904144133
Median Absolute Deviation (MAD)0.2
Skewness1.209795446
Sum31336.5
Variance0.1020100492
MonotonicityNot monotonic
2021-11-29T11:31:18.091208image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.92741
13.7%
1.82459
12.3%
22113
10.6%
1.71793
9.0%
2.11619
8.1%
1.61220
 
6.1%
2.21074
 
5.4%
1.5733
 
3.7%
2.3681
 
3.4%
1.4435
 
2.2%
Other values (48)1589
7.9%
(Missing)3543
17.7%
ValueCountFrequency (%)
0.52
 
< 0.1%
0.61
 
< 0.1%
0.71
 
< 0.1%
0.86
 
< 0.1%
0.915
 
0.1%
137
 
0.2%
1.166
 
0.3%
1.2127
0.6%
1.3250
1.2%
1.351
 
< 0.1%
ValueCountFrequency (%)
6.21
< 0.1%
61
< 0.1%
5.41
< 0.1%
5.11
< 0.1%
51
< 0.1%
4.92
< 0.1%
4.81
< 0.1%
4.51
< 0.1%
4.31
< 0.1%
4.21
< 0.1%

Magnesium-max
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct70
Distinct (%)0.4%
Missing3543
Missing (%)17.7%
Infinite0
Infinite (%)0.0%
Mean2.148046424
Minimum0.5
Maximum9.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:18.189614image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.5
5-th percentile1.6
Q11.9
median2.1
Q32.3
95-th percentile2.8
Maximum9.8
Range9.3
Interquartile range (IQR)0.4

Descriptive statistics

Standard deviation0.4110517987
Coefficient of variation (CV)0.1913607612
Kurtosis30.69868694
Mean2.148046424
Median Absolute Deviation (MAD)0.2
Skewness3.084404281
Sum35350.4
Variance0.1689635812
MonotonicityNot monotonic
2021-11-29T11:31:18.283026image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
22343
11.7%
2.12287
11.4%
2.21991
10.0%
1.91712
8.6%
2.31551
7.8%
1.81258
 
6.3%
2.41091
 
5.5%
2.5811
 
4.1%
1.7754
 
3.8%
2.6511
 
2.6%
Other values (60)2148
10.7%
(Missing)3543
17.7%
ValueCountFrequency (%)
0.51
 
< 0.1%
0.71
 
< 0.1%
0.92
 
< 0.1%
15
 
< 0.1%
1.116
 
0.1%
1.230
 
0.1%
1.365
 
0.3%
1.4126
0.6%
1.451
 
< 0.1%
1.5251
1.3%
ValueCountFrequency (%)
9.81
< 0.1%
9.31
< 0.1%
8.11
< 0.1%
7.91
< 0.1%
7.61
< 0.1%
71
< 0.1%
6.51
< 0.1%
6.41
< 0.1%
6.22
< 0.1%
6.11
< 0.1%

Phosphate-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct125
Distinct (%)1.1%
Missing8365
Missing (%)41.8%
Infinite0
Infinite (%)0.0%
Mean3.240825097
Minimum0.6
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:18.377111image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.6
5-th percentile1.5
Q12.4
median3.1
Q33.8
95-th percentile5.5
Maximum12
Range11.4
Interquartile range (IQR)1.4

Descriptive statistics

Standard deviation1.282144642
Coefficient of variation (CV)0.3956229059
Kurtosis4.757043014
Mean3.240825097
Median Absolute Deviation (MAD)0.7
Skewness1.444106148
Sum37707
Variance1.643894884
MonotonicityNot monotonic
2021-11-29T11:31:18.480098image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3459
 
2.3%
2.9454
 
2.3%
2.8443
 
2.2%
3.2436
 
2.2%
3.1433
 
2.2%
3.4429
 
2.1%
3.3427
 
2.1%
3.5417
 
2.1%
2.5414
 
2.1%
2.4413
 
2.1%
Other values (115)7310
36.5%
(Missing)8365
41.8%
ValueCountFrequency (%)
0.625
 
0.1%
0.716
 
0.1%
0.832
 
0.2%
0.851
 
< 0.1%
0.919
 
0.1%
180
0.4%
1.143
0.2%
1.276
0.4%
1.381
0.4%
1.496
0.5%
ValueCountFrequency (%)
126
< 0.1%
11.81
 
< 0.1%
11.71
 
< 0.1%
11.61
 
< 0.1%
11.51
 
< 0.1%
11.42
 
< 0.1%
11.31
 
< 0.1%
11.21
 
< 0.1%
111
 
< 0.1%
10.91
 
< 0.1%

Phosphate-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct135
Distinct (%)1.2%
Missing8365
Missing (%)41.8%
Infinite0
Infinite (%)0.0%
Mean3.807700902
Minimum0.6
Maximum15.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:18.581056image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.6
5-th percentile2.2
Q13
median3.6
Q34.3
95-th percentile6.3
Maximum15.5
Range14.9
Interquartile range (IQR)1.3

Descriptive statistics

Standard deviation1.357147494
Coefficient of variation (CV)0.3564217697
Kurtosis6.398993699
Mean3.807700902
Median Absolute Deviation (MAD)0.7
Skewness1.839090252
Sum44302.6
Variance1.841849321
MonotonicityNot monotonic
2021-11-29T11:31:18.680920image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.4523
 
2.6%
3.5507
 
2.5%
3.3506
 
2.5%
3.2482
 
2.4%
3.6479
 
2.4%
3.8457
 
2.3%
3.1449
 
2.2%
3.7441
 
2.2%
2.9441
 
2.2%
3433
 
2.2%
Other values (125)6917
34.6%
(Missing)8365
41.8%
ValueCountFrequency (%)
0.63
 
< 0.1%
0.72
 
< 0.1%
0.87
 
< 0.1%
0.92
 
< 0.1%
112
0.1%
1.15
 
< 0.1%
1.212
0.1%
1.319
0.1%
1.413
0.1%
1.527
0.1%
ValueCountFrequency (%)
15.51
 
< 0.1%
14.21
 
< 0.1%
12.71
 
< 0.1%
12.61
 
< 0.1%
12.22
 
< 0.1%
1214
0.1%
11.82
 
< 0.1%
11.63
 
< 0.1%
11.51
 
< 0.1%
11.42
 
< 0.1%

Potassium-min
Real number (ℝ≥0)

MISSING

Distinct242
Distinct (%)1.3%
Missing1434
Missing (%)7.2%
Infinite0
Infinite (%)0.0%
Mean3.804321879
Minimum1.3
Maximum9.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:18.788174image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1.3
5-th percentile3
Q13.5
median3.8
Q34.1
95-th percentile4.6
Maximum9.8
Range8.5
Interquartile range (IQR)0.6

Descriptive statistics

Standard deviation0.5139251116
Coefficient of variation (CV)0.1350898079
Kurtosis6.429641893
Mean3.804321879
Median Absolute Deviation (MAD)0.3
Skewness0.8362609904
Sum70631.04
Variance0.2641190203
MonotonicityNot monotonic
2021-11-29T11:31:18.883936image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.81666
 
8.3%
3.71662
 
8.3%
3.91571
 
7.9%
3.61537
 
7.7%
41320
 
6.6%
3.51269
 
6.3%
4.11140
 
5.7%
3.41070
 
5.3%
4.2872
 
4.4%
3.3858
 
4.3%
Other values (232)5601
28.0%
(Missing)1434
 
7.2%
ValueCountFrequency (%)
1.33
 
< 0.1%
1.42
 
< 0.1%
1.51
 
< 0.1%
1.72
 
< 0.1%
1.81
 
< 0.1%
1.95
 
< 0.1%
27
< 0.1%
2.16
 
< 0.1%
2.215
0.1%
2.317
0.1%
ValueCountFrequency (%)
9.81
 
< 0.1%
9.42
< 0.1%
9.22
< 0.1%
8.21
 
< 0.1%
7.81
 
< 0.1%
7.63
< 0.1%
7.491
 
< 0.1%
7.42
< 0.1%
7.21
 
< 0.1%
7.11
 
< 0.1%

Potassium-max
Real number (ℝ≥0)

MISSING

Distinct278
Distinct (%)1.5%
Missing1434
Missing (%)7.2%
Infinite0
Infinite (%)0.0%
Mean4.325710438
Minimum2.3
Maximum15.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:18.980984image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum2.3
5-th percentile3.5
Q13.9
median4.2
Q34.6
95-th percentile5.5
Maximum15.8
Range13.5
Interquartile range (IQR)0.7

Descriptive statistics

Standard deviation0.72341582
Coefficient of variation (CV)0.1672363026
Kurtosis15.19444244
Mean4.325710438
Median Absolute Deviation (MAD)0.3
Skewness2.574320567
Sum80311.14
Variance0.5233304487
MonotonicityNot monotonic
2021-11-29T11:31:19.089498image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41564
 
7.8%
4.11526
 
7.6%
4.21444
 
7.2%
4.31291
 
6.5%
3.91270
 
6.3%
4.41155
 
5.8%
3.81118
 
5.6%
4.5926
 
4.6%
3.7864
 
4.3%
4.6797
 
4.0%
Other values (268)6611
33.1%
(Missing)1434
 
7.2%
ValueCountFrequency (%)
2.31
 
< 0.1%
2.41
 
< 0.1%
2.53
 
< 0.1%
2.65
 
< 0.1%
2.77
 
< 0.1%
2.811
 
0.1%
2.919
 
0.1%
345
0.2%
3.186
0.4%
3.297
0.5%
ValueCountFrequency (%)
15.81
 
< 0.1%
11.81
 
< 0.1%
11.52
< 0.1%
10.82
< 0.1%
10.751
 
< 0.1%
10.63
< 0.1%
10.42
< 0.1%
10.21
 
< 0.1%
101
 
< 0.1%
9.84
< 0.1%

Bilirubin_total-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct170
Distinct (%)2.0%
Missing11522
Missing (%)57.6%
Infinite0
Infinite (%)0.0%
Mean1.146815287
Minimum0.1
Maximum49.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:19.192433image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.3
Q10.5
median0.7
Q31.1
95-th percentile2.9
Maximum49.2
Range49.1
Interquartile range (IQR)0.6

Descriptive statistics

Standard deviation2.09573636
Coefficient of variation (CV)1.827440203
Kurtosis138.5951719
Mean1.146815287
Median Absolute Deviation (MAD)0.3
Skewness10.10737183
Sum9722.7
Variance4.39211089
MonotonicityNot monotonic
2021-11-29T11:31:19.293658image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.6946
 
4.7%
0.5943
 
4.7%
0.4869
 
4.3%
0.7836
 
4.2%
0.8701
 
3.5%
0.9539
 
2.7%
0.3516
 
2.6%
1466
 
2.3%
1.1347
 
1.7%
1.2260
 
1.3%
Other values (160)2055
 
10.3%
(Missing)11522
57.6%
ValueCountFrequency (%)
0.154
 
0.3%
0.151
 
< 0.1%
0.2219
 
1.1%
0.252
 
< 0.1%
0.3516
2.6%
0.352
 
< 0.1%
0.4869
4.3%
0.452
 
< 0.1%
0.5943
4.7%
0.552
 
< 0.1%
ValueCountFrequency (%)
49.21
< 0.1%
40.32
< 0.1%
36.21
< 0.1%
34.61
< 0.1%
34.31
< 0.1%
29.41
< 0.1%
29.31
< 0.1%
28.21
< 0.1%
27.21
< 0.1%
271
< 0.1%

Bilirubin_total-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct198
Distinct (%)2.3%
Missing11522
Missing (%)57.6%
Infinite0
Infinite (%)0.0%
Mean1.372605567
Minimum0.1
Maximum49.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:19.391795image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.3
Q10.6
median0.8
Q31.3
95-th percentile3.6
Maximum49.6
Range49.5
Interquartile range (IQR)0.7

Descriptive statistics

Standard deviation2.636673757
Coefficient of variation (CV)1.920926025
Kurtosis112.3733259
Mean1.372605567
Median Absolute Deviation (MAD)0.3
Skewness9.205650692
Sum11636.95
Variance6.952048501
MonotonicityNot monotonic
2021-11-29T11:31:19.577483image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.6851
 
4.3%
0.5828
 
4.1%
0.7823
 
4.1%
0.8698
 
3.5%
0.4686
 
3.4%
0.9599
 
3.0%
1499
 
2.5%
1.1384
 
1.9%
0.3376
 
1.9%
1.2319
 
1.6%
Other values (188)2415
 
12.1%
(Missing)11522
57.6%
ValueCountFrequency (%)
0.130
 
0.1%
0.151
 
< 0.1%
0.2147
 
0.7%
0.251
 
< 0.1%
0.3376
1.9%
0.352
 
< 0.1%
0.4686
3.4%
0.451
 
< 0.1%
0.5828
4.1%
0.551
 
< 0.1%
ValueCountFrequency (%)
49.62
< 0.1%
49.21
< 0.1%
45.31
< 0.1%
42.91
< 0.1%
40.91
< 0.1%
38.81
< 0.1%
37.51
< 0.1%
36.51
< 0.1%
34.71
< 0.1%
341
< 0.1%

TroponinI-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct972
Distinct (%)14.8%
Missing13436
Missing (%)67.2%
Infinite0
Infinite (%)0.0%
Mean3.581375686
Minimum0.01
Maximum349.05
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:19.676317image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.01
Q10.02
median0.06
Q30.56
95-th percentile21.1825
Maximum349.05
Range349.04
Interquartile range (IQR)0.54

Descriptive statistics

Standard deviation14.32076588
Coefficient of variation (CV)3.998677362
Kurtosis117.394797
Mean3.581375686
Median Absolute Deviation (MAD)0.05
Skewness8.817558162
Sum23508.15
Variance205.0843353
MonotonicityNot monotonic
2021-11-29T11:31:19.773060image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.011342
 
6.7%
0.03894
 
4.5%
0.04334
 
1.7%
0.02332
 
1.7%
0.05215
 
1.1%
0.06188
 
0.9%
0.07160
 
0.8%
0.08126
 
0.6%
0.09111
 
0.6%
0.192
 
0.5%
Other values (962)2770
 
13.9%
(Missing)13436
67.2%
ValueCountFrequency (%)
0.011342
6.7%
0.02332
 
1.7%
0.03894
4.5%
0.04334
 
1.7%
0.05215
 
1.1%
0.06188
 
0.9%
0.07160
 
0.8%
0.08126
 
0.6%
0.09111
 
0.6%
0.192
 
0.5%
ValueCountFrequency (%)
349.051
 
< 0.1%
219.621
 
< 0.1%
2005
< 0.1%
180.081
 
< 0.1%
1671
 
< 0.1%
164.531
 
< 0.1%
155.651
 
< 0.1%
153.341
 
< 0.1%
151.831
 
< 0.1%
149.341
 
< 0.1%

TroponinI-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct1143
Distinct (%)17.4%
Missing13436
Missing (%)67.2%
Infinite0
Infinite (%)0.0%
Mean6.66932663
Minimum0.01
Maximum440
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:19.877745image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.01
Q10.03
median0.09
Q31
95-th percentile40
Maximum440
Range439.99
Interquartile range (IQR)0.97

Descriptive statistics

Standard deviation25.55908401
Coefficient of variation (CV)3.832333522
Kurtosis72.44230041
Mean6.66932663
Median Absolute Deviation (MAD)0.08
Skewness7.321145882
Sum43777.46
Variance653.2667757
MonotonicityNot monotonic
2021-11-29T11:31:19.973097image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.011209
 
6.0%
0.03818
 
4.1%
0.02346
 
1.7%
0.04273
 
1.4%
0.05187
 
0.9%
0.06167
 
0.8%
0.07163
 
0.8%
0.08115
 
0.6%
0.1109
 
0.5%
0.0999
 
0.5%
Other values (1133)3078
 
15.4%
(Missing)13436
67.2%
ValueCountFrequency (%)
0.011209
6.0%
0.02346
 
1.7%
0.03818
4.1%
0.04273
 
1.4%
0.05187
 
0.9%
0.06167
 
0.8%
0.07163
 
0.8%
0.08115
 
0.6%
0.0999
 
0.5%
0.1109
 
0.5%
ValueCountFrequency (%)
4402
 
< 0.1%
394.031
 
< 0.1%
381.61
 
< 0.1%
325.311
 
< 0.1%
271.61
 
< 0.1%
243.811
 
< 0.1%
235.881
 
< 0.1%
226.781
 
< 0.1%
20034
0.2%
199.411
 
< 0.1%

Hct-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct436
Distinct (%)2.4%
Missing1953
Missing (%)9.8%
Infinite0
Infinite (%)0.0%
Mean31.26301213
Minimum9.1
Maximum65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:20.070625image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum9.1
5-th percentile20.4
Q126.2
median31.3
Q336.2
95-th percentile42.2
Maximum65
Range55.9
Interquartile range (IQR)10

Descriptive statistics

Standard deviation6.804708332
Coefficient of variation (CV)0.2176600355
Kurtosis-0.3645388506
Mean31.26301213
Median Absolute Deviation (MAD)5
Skewness0.08356011901
Sum564203.58
Variance46.30405548
MonotonicityNot monotonic
2021-11-29T11:31:20.163813image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33113
 
0.6%
34111
 
0.6%
32.4110
 
0.5%
32.9109
 
0.5%
37.3105
 
0.5%
27104
 
0.5%
34.3104
 
0.5%
30.1103
 
0.5%
29103
 
0.5%
24103
 
0.5%
Other values (426)16982
84.9%
(Missing)1953
 
9.8%
ValueCountFrequency (%)
9.11
< 0.1%
9.31
< 0.1%
9.61
< 0.1%
10.71
< 0.1%
10.81
< 0.1%
11.51
< 0.1%
11.61
< 0.1%
12.41
< 0.1%
12.62
< 0.1%
12.72
< 0.1%
ValueCountFrequency (%)
651
< 0.1%
63.41
< 0.1%
63.21
< 0.1%
58.81
< 0.1%
57.71
< 0.1%
56.11
< 0.1%
55.61
< 0.1%
55.31
< 0.1%
55.21
< 0.1%
54.91
< 0.1%

Hct-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct398
Distinct (%)2.2%
Missing1953
Missing (%)9.8%
Infinite0
Infinite (%)0.0%
Mean33.73967031
Minimum9.3
Maximum70.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:20.261185image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum9.3
5-th percentile24.5
Q129.1
median33.4
Q337.9
95-th percentile43.9
Maximum70.2
Range60.9
Interquartile range (IQR)8.8

Descriptive statistics

Standard deviation6.042713362
Coefficient of variation (CV)0.1790981746
Kurtosis-0.04736581214
Mean33.73967031
Median Absolute Deviation (MAD)4.4
Skewness0.3138012684
Sum608899.83
Variance36.51438478
MonotonicityNot monotonic
2021-11-29T11:31:20.357055image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34138
 
0.7%
36.1125
 
0.6%
33125
 
0.6%
29.1124
 
0.6%
34.6124
 
0.6%
33.4121
 
0.6%
32.1118
 
0.6%
33.5117
 
0.6%
29117
 
0.6%
35116
 
0.6%
Other values (388)16822
84.1%
(Missing)1953
 
9.8%
ValueCountFrequency (%)
9.31
 
< 0.1%
13.31
 
< 0.1%
14.41
 
< 0.1%
14.61
 
< 0.1%
15.51
 
< 0.1%
161
 
< 0.1%
16.71
 
< 0.1%
16.91
 
< 0.1%
17.41
 
< 0.1%
18.13
< 0.1%
ValueCountFrequency (%)
70.21
 
< 0.1%
653
< 0.1%
621
 
< 0.1%
61.21
 
< 0.1%
60.21
 
< 0.1%
59.11
 
< 0.1%
591
 
< 0.1%
581
 
< 0.1%
57.41
 
< 0.1%
57.31
 
< 0.1%

Hgb-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct216
Distinct (%)1.2%
Missing1941
Missing (%)9.7%
Infinite0
Infinite (%)0.0%
Mean10.23865829
Minimum2.3
Maximum26.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:20.456440image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum2.3
5-th percentile6.7
Q18.5
median10.2
Q311.9
95-th percentile14.1
Maximum26.6
Range24.3
Interquartile range (IQR)3.4

Descriptive statistics

Standard deviation2.330054737
Coefficient of variation (CV)0.2275742262
Kurtosis0.09243264671
Mean10.23865829
Median Absolute Deviation (MAD)1.7
Skewness0.2868288395
Sum184899.93
Variance5.429155078
MonotonicityNot monotonic
2021-11-29T11:31:20.555084image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9.9298
 
1.5%
10.5297
 
1.5%
9.1285
 
1.4%
10.9284
 
1.4%
9283
 
1.4%
10.7280
 
1.4%
10.3279
 
1.4%
9.2278
 
1.4%
11.3277
 
1.4%
9.4275
 
1.4%
Other values (206)15223
76.1%
(Missing)1941
 
9.7%
ValueCountFrequency (%)
2.31
 
< 0.1%
2.61
 
< 0.1%
2.81
 
< 0.1%
2.91
 
< 0.1%
31
 
< 0.1%
3.62
< 0.1%
3.72
< 0.1%
3.83
< 0.1%
3.91
 
< 0.1%
43
< 0.1%
ValueCountFrequency (%)
26.61
< 0.1%
24.82
< 0.1%
23.81
< 0.1%
23.41
< 0.1%
21.61
< 0.1%
21.21
< 0.1%
211
< 0.1%
20.61
< 0.1%
20.31
< 0.1%
19.61
< 0.1%

Hgb-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct207
Distinct (%)1.1%
Missing1941
Missing (%)9.7%
Infinite0
Infinite (%)0.0%
Mean11.11210089
Minimum2.6
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:20.652812image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum2.6
5-th percentile8
Q19.5
median10.9
Q312.5
95-th percentile14.8
Maximum30
Range27.4
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.168950085
Coefficient of variation (CV)0.1951881203
Kurtosis1.340921459
Mean11.11210089
Median Absolute Deviation (MAD)1.5
Skewness0.6569832784
Sum200673.43
Variance4.704344473
MonotonicityNot monotonic
2021-11-29T11:31:20.746761image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.1333
 
1.7%
10.8332
 
1.7%
11.3326
 
1.6%
10.5321
 
1.6%
9.2320
 
1.6%
10.7316
 
1.6%
11.2316
 
1.6%
10.9315
 
1.6%
11.7312
 
1.6%
10.2312
 
1.6%
Other values (197)14856
74.3%
(Missing)1941
 
9.7%
ValueCountFrequency (%)
2.61
< 0.1%
41
< 0.1%
4.31
< 0.1%
4.51
< 0.1%
4.81
< 0.1%
4.91
< 0.1%
5.11
< 0.1%
5.51
< 0.1%
5.62
< 0.1%
5.71
< 0.1%
ValueCountFrequency (%)
301
 
< 0.1%
26.61
 
< 0.1%
251
 
< 0.1%
24.82
< 0.1%
241
 
< 0.1%
23.82
< 0.1%
23.63
< 0.1%
23.41
 
< 0.1%
23.21
 
< 0.1%
22.41
 
< 0.1%

PTT-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct566
Distinct (%)12.9%
Missing15602
Missing (%)78.0%
Infinite0
Infinite (%)0.0%
Mean35.85675307
Minimum20
Maximum250
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:20.844447image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile23.3
Q127.4
median30.5
Q335.3
95-th percentile62.5
Maximum250
Range230
Interquartile range (IQR)7.9

Descriptive statistics

Standard deviation22.81357629
Coefficient of variation (CV)0.6362421116
Kurtosis43.9425364
Mean35.85675307
Median Absolute Deviation (MAD)3.6
Skewness5.941973984
Sum157698
Variance520.459263
MonotonicityNot monotonic
2021-11-29T11:31:20.943588image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27.346
 
0.2%
2845
 
0.2%
29.645
 
0.2%
30.745
 
0.2%
3044
 
0.2%
30.843
 
0.2%
30.443
 
0.2%
27.440
 
0.2%
31.340
 
0.2%
31.739
 
0.2%
Other values (556)3968
 
19.8%
(Missing)15602
78.0%
ValueCountFrequency (%)
2038
0.2%
20.15
 
< 0.1%
20.32
 
< 0.1%
20.43
 
< 0.1%
20.53
 
< 0.1%
20.64
 
< 0.1%
20.71
 
< 0.1%
20.83
 
< 0.1%
20.97
 
< 0.1%
214
 
< 0.1%
ValueCountFrequency (%)
2503
 
< 0.1%
249.94
 
< 0.1%
24912
0.1%
237.51
 
< 0.1%
216.51
 
< 0.1%
212.31
 
< 0.1%
204.91
 
< 0.1%
200.81
 
< 0.1%
196.81
 
< 0.1%
195.51
 
< 0.1%

PTT-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct747
Distinct (%)17.0%
Missing15602
Missing (%)78.0%
Infinite0
Infinite (%)0.0%
Mean44.49657799
Minimum20
Maximum250
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:21.126722image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile24.2
Q128.4
median32
Q340.3
95-th percentile119.7125
Maximum250
Range230
Interquartile range (IQR)11.9

Descriptive statistics

Standard deviation39.26047598
Coefficient of variation (CV)0.8823257372
Kurtosis15.02148047
Mean44.49657799
Median Absolute Deviation (MAD)4.7
Skewness3.779902636
Sum195695.95
Variance1541.384974
MonotonicityNot monotonic
2021-11-29T11:31:21.225201image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24956
 
0.3%
28.941
 
0.2%
28.839
 
0.2%
30.838
 
0.2%
2836
 
0.2%
27.336
 
0.2%
30.736
 
0.2%
28.636
 
0.2%
29.735
 
0.2%
31.335
 
0.2%
Other values (737)4010
 
20.1%
(Missing)15602
78.0%
ValueCountFrequency (%)
2021
0.1%
20.13
 
< 0.1%
20.31
 
< 0.1%
20.43
 
< 0.1%
20.52
 
< 0.1%
20.62
 
< 0.1%
20.71
 
< 0.1%
20.83
 
< 0.1%
20.95
 
< 0.1%
214
 
< 0.1%
ValueCountFrequency (%)
25010
 
0.1%
249.913
 
0.1%
24956
0.3%
248.71
 
< 0.1%
2481
 
< 0.1%
247.51
 
< 0.1%
2472
 
< 0.1%
246.81
 
< 0.1%
238.11
 
< 0.1%
237.51
 
< 0.1%

WBC-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct405
Distinct (%)2.2%
Missing2000
Missing (%)10.0%
Infinite0
Infinite (%)0.0%
Mean9.320386667
Minimum0.1
Maximum296.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:21.323124image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile3.9
Q16.3
median8.5
Q311.2
95-th percentile16.9
Maximum296.1
Range296
Interquartile range (IQR)4.9

Descriptive statistics

Standard deviation5.69375804
Coefficient of variation (CV)0.6108929
Kurtosis491.5408061
Mean9.320386667
Median Absolute Deviation (MAD)2.4
Skewness13.90233237
Sum167766.96
Variance32.41888062
MonotonicityNot monotonic
2021-11-29T11:31:21.417173image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.2250
 
1.2%
7239
 
1.2%
7.4238
 
1.2%
8.6232
 
1.2%
7.6230
 
1.1%
7.8229
 
1.1%
8224
 
1.1%
6222
 
1.1%
6.4222
 
1.1%
8.2219
 
1.1%
Other values (395)15695
78.5%
(Missing)2000
 
10.0%
ValueCountFrequency (%)
0.112
0.1%
0.24
 
< 0.1%
0.33
 
< 0.1%
0.45
< 0.1%
0.52
 
< 0.1%
0.64
 
< 0.1%
0.75
< 0.1%
0.82
 
< 0.1%
0.93
 
< 0.1%
15
< 0.1%
ValueCountFrequency (%)
296.11
< 0.1%
152.91
< 0.1%
150.61
< 0.1%
144.91
< 0.1%
142.21
< 0.1%
140.41
< 0.1%
137.71
< 0.1%
119.51
< 0.1%
1181
< 0.1%
104.11
< 0.1%

WBC-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct481
Distinct (%)2.7%
Missing2000
Missing (%)10.0%
Infinite0
Infinite (%)0.0%
Mean11.40393778
Minimum0.1
Maximum440
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:21.521235image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile4.6
Q17.5
median10.2
Q313.7
95-th percentile21.3
Maximum440
Range439.9
Interquartile range (IQR)6.2

Descriptive statistics

Standard deviation8.307665789
Coefficient of variation (CV)0.7284909783
Kurtosis747.5277041
Mean11.40393778
Median Absolute Deviation (MAD)3
Skewness19.03370792
Sum205270.88
Variance69.01731086
MonotonicityNot monotonic
2021-11-29T11:31:21.614094image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.6202
 
1.0%
8.2196
 
1.0%
8.8195
 
1.0%
7.4194
 
1.0%
8186
 
0.9%
10186
 
0.9%
7.8186
 
0.9%
9.4183
 
0.9%
9.2180
 
0.9%
10.4180
 
0.9%
Other values (471)16112
80.6%
(Missing)2000
 
10.0%
ValueCountFrequency (%)
0.19
< 0.1%
0.23
 
< 0.1%
0.33
 
< 0.1%
0.45
< 0.1%
0.52
 
< 0.1%
0.63
 
< 0.1%
0.81
 
< 0.1%
0.93
 
< 0.1%
11
 
< 0.1%
1.12
 
< 0.1%
ValueCountFrequency (%)
4401
< 0.1%
3871
< 0.1%
2511
< 0.1%
215.31
< 0.1%
199.21
< 0.1%
182.61
< 0.1%
169.71
< 0.1%
166.21
< 0.1%
152.91
< 0.1%
144.91
< 0.1%

Fibrinogen-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct518
Distinct (%)26.6%
Missing18052
Missing (%)90.3%
Infinite0
Infinite (%)0.0%
Mean270.0433778
Minimum35
Maximum1000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:21.711349image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum35
5-th percentile101.35
Q1176
median233
Q3324
95-th percentile573.15
Maximum1000
Range965
Interquartile range (IQR)148

Descriptive statistics

Standard deviation146.7863663
Coefficient of variation (CV)0.54356588
Kurtosis3.861013099
Mean270.0433778
Median Absolute Deviation (MAD)71
Skewness1.657538313
Sum526044.5
Variance21546.23733
MonotonicityNot monotonic
2021-11-29T11:31:21.813444image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21722
 
0.1%
20018
 
0.1%
23015
 
0.1%
21315
 
0.1%
24014
 
0.1%
15114
 
0.1%
21914
 
0.1%
20214
 
0.1%
21413
 
0.1%
20813
 
0.1%
Other values (508)1796
 
9.0%
(Missing)18052
90.3%
ValueCountFrequency (%)
358
< 0.1%
411
 
< 0.1%
422
 
< 0.1%
463
 
< 0.1%
482
 
< 0.1%
501
 
< 0.1%
512
 
< 0.1%
524
< 0.1%
531
 
< 0.1%
571
 
< 0.1%
ValueCountFrequency (%)
10006
< 0.1%
9541
 
< 0.1%
9451
 
< 0.1%
9191
 
< 0.1%
9121
 
< 0.1%
8881
 
< 0.1%
8821
 
< 0.1%
8781
 
< 0.1%
8671
 
< 0.1%
8361
 
< 0.1%

Fibrinogen-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct539
Distinct (%)27.7%
Missing18052
Missing (%)90.3%
Infinite0
Infinite (%)0.0%
Mean322.0056468
Minimum35
Maximum1179
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:21.912916image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum35
5-th percentile147.35
Q1217
median288
Q3386
95-th percentile636.3
Maximum1179
Range1144
Interquartile range (IQR)169

Descriptive statistics

Standard deviation154.5451557
Coefficient of variation (CV)0.4799454831
Kurtosis3.148556483
Mean322.0056468
Median Absolute Deviation (MAD)80
Skewness1.529860586
Sum627267
Variance23884.20516
MonotonicityNot monotonic
2021-11-29T11:31:22.014410image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21720
 
0.1%
20015
 
0.1%
23014
 
0.1%
30513
 
0.1%
23613
 
0.1%
33413
 
0.1%
20813
 
0.1%
28012
 
0.1%
22912
 
0.1%
21512
 
0.1%
Other values (529)1811
 
9.1%
(Missing)18052
90.3%
ValueCountFrequency (%)
351
< 0.1%
581
< 0.1%
612
< 0.1%
621
< 0.1%
651
< 0.1%
701
< 0.1%
711
< 0.1%
761
< 0.1%
812
< 0.1%
861
< 0.1%
ValueCountFrequency (%)
11791
 
< 0.1%
10008
< 0.1%
9661
 
< 0.1%
9542
 
< 0.1%
9451
 
< 0.1%
9321
 
< 0.1%
9191
 
< 0.1%
9121
 
< 0.1%
9011
 
< 0.1%
8971
 
< 0.1%

Platelets-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct624
Distinct (%)3.5%
Missing1992
Missing (%)10.0%
Infinite0
Infinite (%)0.0%
Mean190.2616892
Minimum1
Maximum2322
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:22.114375image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile65
Q1129
median180
Q3238
95-th percentile348.65
Maximum2322
Range2321
Interquartile range (IQR)109

Descriptive statistics

Standard deviation92.41697197
Coefficient of variation (CV)0.4857361056
Kurtosis19.13541482
Mean190.2616892
Median Absolute Deviation (MAD)54
Skewness1.846470537
Sum3426232.5
Variance8540.896709
MonotonicityNot monotonic
2021-11-29T11:31:22.213371image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
180109
 
0.5%
141109
 
0.5%
183107
 
0.5%
162105
 
0.5%
166105
 
0.5%
167102
 
0.5%
168101
 
0.5%
175101
 
0.5%
159101
 
0.5%
18298
 
0.5%
Other values (614)16970
84.9%
(Missing)1992
 
10.0%
ValueCountFrequency (%)
11
 
< 0.1%
24
< 0.1%
32
 
< 0.1%
47
< 0.1%
52
 
< 0.1%
61
 
< 0.1%
72
 
< 0.1%
83
< 0.1%
92
 
< 0.1%
101
 
< 0.1%
ValueCountFrequency (%)
23221
< 0.1%
9201
< 0.1%
8381
< 0.1%
8221
< 0.1%
8111
< 0.1%
8061
< 0.1%
8031
< 0.1%
7921
< 0.1%
7821
< 0.1%
7731
< 0.1%

Platelets-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct651
Distinct (%)3.6%
Missing1992
Missing (%)10.0%
Infinite0
Infinite (%)0.0%
Mean212.581908
Minimum4
Maximum2322
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:22.311868image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile88
Q1149
median199.5
Q3259
95-th percentile378.65
Maximum2322
Range2318
Interquartile range (IQR)110

Descriptive statistics

Standard deviation96.25496857
Coefficient of variation (CV)0.4527900303
Kurtosis17.39453052
Mean212.581908
Median Absolute Deviation (MAD)54.5
Skewness1.946998427
Sum3828175
Variance9265.018975
MonotonicityNot monotonic
2021-11-29T11:31:22.410643image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
167112
 
0.6%
206104
 
0.5%
178102
 
0.5%
175102
 
0.5%
204100
 
0.5%
18799
 
0.5%
20299
 
0.5%
17399
 
0.5%
15898
 
0.5%
17698
 
0.5%
Other values (641)16995
85.0%
(Missing)1992
 
10.0%
ValueCountFrequency (%)
42
< 0.1%
53
< 0.1%
61
 
< 0.1%
72
< 0.1%
81
 
< 0.1%
91
 
< 0.1%
113
< 0.1%
131
 
< 0.1%
141
 
< 0.1%
151
 
< 0.1%
ValueCountFrequency (%)
23221
< 0.1%
11401
< 0.1%
10361
< 0.1%
9841
< 0.1%
9651
< 0.1%
9321
< 0.1%
9071
< 0.1%
8691
< 0.1%
8651
< 0.1%
8541
< 0.1%

Age-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct77
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean60.6488
Minimum14
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:22.513102image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum14
5-th percentile30
Q150
median62
Q372
95-th percentile85
Maximum100
Range86
Interquartile range (IQR)22

Descriptive statistics

Standard deviation16.67181022
Coefficient of variation (CV)0.2748910155
Kurtosis-0.1562598942
Mean60.6488
Median Absolute Deviation (MAD)11
Skewness-0.2649819802
Sum1212976
Variance277.949256
MonotonicityNot monotonic
2021-11-29T11:31:22.693675image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
67572
 
2.9%
68539
 
2.7%
66512
 
2.6%
65510
 
2.5%
61498
 
2.5%
69495
 
2.5%
71481
 
2.4%
62477
 
2.4%
63470
 
2.4%
70467
 
2.3%
Other values (67)14979
74.9%
ValueCountFrequency (%)
142
 
< 0.1%
152
 
< 0.1%
165
 
< 0.1%
1713
 
0.1%
1832
 
0.2%
1954
0.3%
2065
0.3%
2199
0.5%
2259
0.3%
2377
0.4%
ValueCountFrequency (%)
100392
2.0%
89111
 
0.6%
88138
 
0.7%
87145
 
0.7%
86187
0.9%
85187
0.9%
84206
1.0%
83247
1.2%
82242
1.2%
81224
1.1%

Age-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct77
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean60.6488
Minimum14
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:22.793722image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum14
5-th percentile30
Q150
median62
Q372
95-th percentile85
Maximum100
Range86
Interquartile range (IQR)22

Descriptive statistics

Standard deviation16.67181022
Coefficient of variation (CV)0.2748910155
Kurtosis-0.1562598942
Mean60.6488
Median Absolute Deviation (MAD)11
Skewness-0.2649819802
Sum1212976
Variance277.949256
MonotonicityNot monotonic
2021-11-29T11:31:22.887619image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
67572
 
2.9%
68539
 
2.7%
66512
 
2.6%
65510
 
2.5%
61498
 
2.5%
69495
 
2.5%
71481
 
2.4%
62477
 
2.4%
63470
 
2.4%
70467
 
2.3%
Other values (67)14979
74.9%
ValueCountFrequency (%)
142
 
< 0.1%
152
 
< 0.1%
165
 
< 0.1%
1713
 
0.1%
1832
 
0.2%
1954
0.3%
2065
0.3%
2199
0.5%
2259
0.3%
2377
0.4%
ValueCountFrequency (%)
100392
2.0%
89111
 
0.6%
88138
 
0.7%
87145
 
0.7%
86187
0.9%
85187
0.9%
84206
1.0%
83247
1.2%
82242
1.2%
81224
1.1%

Gender-min
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.4 KiB
1
10732 
0
9268 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters20000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
110732
53.7%
09268
46.3%

Length

2021-11-29T11:31:22.977473image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T11:31:23.022102image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
110732
53.7%
09268
46.3%

Most occurring characters

ValueCountFrequency (%)
110732
53.7%
09268
46.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number20000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
110732
53.7%
09268
46.3%

Most occurring scripts

ValueCountFrequency (%)
Common20000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
110732
53.7%
09268
46.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII20000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
110732
53.7%
09268
46.3%

Gender-max
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.4 KiB
1
10732 
0
9268 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters20000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
110732
53.7%
09268
46.3%

Length

2021-11-29T11:31:23.475862image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T11:31:23.528779image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
110732
53.7%
09268
46.3%

Most occurring characters

ValueCountFrequency (%)
110732
53.7%
09268
46.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number20000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
110732
53.7%
09268
46.3%

Most occurring scripts

ValueCountFrequency (%)
Common20000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
110732
53.7%
09268
46.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII20000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
110732
53.7%
09268
46.3%

Unit1-min
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct2
Distinct (%)< 0.1%
Missing6095
Missing (%)30.5%
Memory size156.4 KiB
0.0
6982 
1.0
6923 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters41715
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row0.0
3rd row1.0
4th row1.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.06982
34.9%
1.06923
34.6%
(Missing)6095
30.5%

Length

2021-11-29T11:31:23.583938image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T11:31:23.635620image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
0.06982
50.2%
1.06923
49.8%

Most occurring characters

ValueCountFrequency (%)
020887
50.1%
.13905
33.3%
16923
 
16.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number27810
66.7%
Other Punctuation13905
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
020887
75.1%
16923
 
24.9%
Other Punctuation
ValueCountFrequency (%)
.13905
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common41715
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
020887
50.1%
.13905
33.3%
16923
 
16.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII41715
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
020887
50.1%
.13905
33.3%
16923
 
16.6%

Unit1-max
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct2
Distinct (%)< 0.1%
Missing6095
Missing (%)30.5%
Memory size156.4 KiB
0.0
6982 
1.0
6923 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters41715
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row0.0
3rd row1.0
4th row1.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.06982
34.9%
1.06923
34.6%
(Missing)6095
30.5%

Length

2021-11-29T11:31:23.691038image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T11:31:23.742775image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
0.06982
50.2%
1.06923
49.8%

Most occurring characters

ValueCountFrequency (%)
020887
50.1%
.13905
33.3%
16923
 
16.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number27810
66.7%
Other Punctuation13905
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
020887
75.1%
16923
 
24.9%
Other Punctuation
ValueCountFrequency (%)
.13905
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common41715
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
020887
50.1%
.13905
33.3%
16923
 
16.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII41715
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
020887
50.1%
.13905
33.3%
16923
 
16.6%

Unit2-min
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct2
Distinct (%)< 0.1%
Missing6095
Missing (%)30.5%
Memory size156.4 KiB
1.0
6982 
0.0
6923 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters41715
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row1.0
3rd row0.0
4th row0.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.06982
34.9%
0.06923
34.6%
(Missing)6095
30.5%

Length

2021-11-29T11:31:23.797872image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T11:31:23.849498image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
1.06982
50.2%
0.06923
49.8%

Most occurring characters

ValueCountFrequency (%)
020828
49.9%
.13905
33.3%
16982
 
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number27810
66.7%
Other Punctuation13905
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
020828
74.9%
16982
 
25.1%
Other Punctuation
ValueCountFrequency (%)
.13905
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common41715
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
020828
49.9%
.13905
33.3%
16982
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII41715
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
020828
49.9%
.13905
33.3%
16982
 
16.7%

Unit2-max
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct2
Distinct (%)< 0.1%
Missing6095
Missing (%)30.5%
Memory size156.4 KiB
1.0
6982 
0.0
6923 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters41715
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row1.0
3rd row0.0
4th row0.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.06982
34.9%
0.06923
34.6%
(Missing)6095
30.5%

Length

2021-11-29T11:31:23.904109image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T11:31:23.955811image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
1.06982
50.2%
0.06923
49.8%

Most occurring characters

ValueCountFrequency (%)
020828
49.9%
.13905
33.3%
16982
 
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number27810
66.7%
Other Punctuation13905
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
020828
74.9%
16982
 
25.1%
Other Punctuation
ValueCountFrequency (%)
.13905
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common41715
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
020828
49.9%
.13905
33.3%
16982
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII41715
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
020828
49.9%
.13905
33.3%
16982
 
16.7%

HospAdmTime-min
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct7975
Distinct (%)39.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-55.072586
Minimum-5366.86
Maximum0
Zeros1145
Zeros (%)5.7%
Negative18855
Negative (%)94.3%
Memory size156.4 KiB
2021-11-29T11:31:24.016991image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-5366.86
5-th percentile-244.829
Q1-52.3525
median-8.57
Q3-3.38
95-th percentile0
Maximum0
Range5366.86
Interquartile range (IQR)48.9725

Descriptive statistics

Standard deviation135.5956936
Coefficient of variation (CV)-2.462126867
Kurtosis241.4449376
Mean-55.072586
Median Absolute Deviation (MAD)8.52
Skewness-10.8324003
Sum-1101451.72
Variance18386.19213
MonotonicityNot monotonic
2021-11-29T11:31:24.122267image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
01145
 
5.7%
-0.02250
 
1.2%
-0.03197
 
1.0%
-0.01179
 
0.9%
-0.04136
 
0.7%
-0.05122
 
0.6%
-0.06105
 
0.5%
-0.0794
 
0.5%
-0.0976
 
0.4%
-0.0859
 
0.3%
Other values (7965)17637
88.2%
ValueCountFrequency (%)
-5366.861
< 0.1%
-3397.641
< 0.1%
-3342.341
< 0.1%
-3189.391
< 0.1%
-3112.121
< 0.1%
-2929.371
< 0.1%
-2842.111
< 0.1%
-2667.341
< 0.1%
-2384.781
< 0.1%
-2382.341
< 0.1%
ValueCountFrequency (%)
01145
5.7%
-0.01179
 
0.9%
-0.02250
 
1.2%
-0.03197
 
1.0%
-0.04136
 
0.7%
-0.05122
 
0.6%
-0.06105
 
0.5%
-0.0794
 
0.5%
-0.0859
 
0.3%
-0.0976
 
0.4%

HospAdmTime-max
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct7975
Distinct (%)39.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-55.072586
Minimum-5366.86
Maximum0
Zeros1145
Zeros (%)5.7%
Negative18855
Negative (%)94.3%
Memory size156.4 KiB
2021-11-29T11:31:24.225769image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-5366.86
5-th percentile-244.829
Q1-52.3525
median-8.57
Q3-3.38
95-th percentile0
Maximum0
Range5366.86
Interquartile range (IQR)48.9725

Descriptive statistics

Standard deviation135.5956936
Coefficient of variation (CV)-2.462126867
Kurtosis241.4449376
Mean-55.072586
Median Absolute Deviation (MAD)8.52
Skewness-10.8324003
Sum-1101451.72
Variance18386.19213
MonotonicityNot monotonic
2021-11-29T11:31:24.330693image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
01145
 
5.7%
-0.02250
 
1.2%
-0.03197
 
1.0%
-0.01179
 
0.9%
-0.04136
 
0.7%
-0.05122
 
0.6%
-0.06105
 
0.5%
-0.0794
 
0.5%
-0.0976
 
0.4%
-0.0859
 
0.3%
Other values (7965)17637
88.2%
ValueCountFrequency (%)
-5366.861
< 0.1%
-3397.641
< 0.1%
-3342.341
< 0.1%
-3189.391
< 0.1%
-3112.121
< 0.1%
-2929.371
< 0.1%
-2842.111
< 0.1%
-2667.341
< 0.1%
-2384.781
< 0.1%
-2382.341
< 0.1%
ValueCountFrequency (%)
01145
5.7%
-0.01179
 
0.9%
-0.02250
 
1.2%
-0.03197
 
1.0%
-0.04136
 
0.7%
-0.05122
 
0.6%
-0.06105
 
0.5%
-0.0794
 
0.5%
-0.0859
 
0.3%
-0.0976
 
0.4%

ICULOS-min
Real number (ℝ≥0)

Distinct17
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.13345
Minimum1
Maximum26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:24.419170image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile2
Maximum26
Range25
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.6983304954
Coefficient of variation (CV)0.6161105434
Kurtosis213.6472826
Mean1.13345
Median Absolute Deviation (MAD)0
Skewness10.72522731
Sum22669
Variance0.4876654808
MonotonicityNot monotonic
2021-11-29T11:31:24.496851image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
118704
93.5%
2741
 
3.7%
3219
 
1.1%
4146
 
0.7%
577
 
0.4%
654
 
0.3%
725
 
0.1%
814
 
0.1%
97
 
< 0.1%
133
 
< 0.1%
Other values (7)10
 
0.1%
ValueCountFrequency (%)
118704
93.5%
2741
 
3.7%
3219
 
1.1%
4146
 
0.7%
577
 
0.4%
654
 
0.3%
725
 
0.1%
814
 
0.1%
97
 
< 0.1%
103
 
< 0.1%
ValueCountFrequency (%)
261
 
< 0.1%
251
 
< 0.1%
151
 
< 0.1%
141
 
< 0.1%
133
 
< 0.1%
121
 
< 0.1%
112
 
< 0.1%
103
 
< 0.1%
97
< 0.1%
814
0.1%

ICULOS-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct229
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.2332
Minimum8
Maximum336
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:24.680629image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile14
Q123
median38
Q347
95-th percentile58
Maximum336
Range328
Interquartile range (IQR)24

Descriptive statistics

Standard deviation23.2718112
Coefficient of variation (CV)0.6086807069
Kurtosis44.09947372
Mean38.2332
Median Absolute Deviation (MAD)12
Skewness4.971265249
Sum764664
Variance541.5771966
MonotonicityNot monotonic
2021-11-29T11:31:24.780511image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
39684
 
3.4%
40671
 
3.4%
36669
 
3.3%
38667
 
3.3%
41638
 
3.2%
43611
 
3.1%
42597
 
3.0%
37580
 
2.9%
21563
 
2.8%
44558
 
2.8%
Other values (219)13762
68.8%
ValueCountFrequency (%)
8193
1.0%
9105
 
0.5%
10116
 
0.6%
11111
 
0.6%
12151
0.8%
13190
0.9%
14214
1.1%
15319
1.6%
16330
1.7%
17360
1.8%
ValueCountFrequency (%)
3367
< 0.1%
3351
 
< 0.1%
3341
 
< 0.1%
3271
 
< 0.1%
3261
 
< 0.1%
3201
 
< 0.1%
3181
 
< 0.1%
3122
 
< 0.1%
3102
 
< 0.1%
3081
 
< 0.1%

SepsisLabel-min
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.4 KiB
0
19777 
1
 
223

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters20000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
019777
98.9%
1223
 
1.1%

Length

2021-11-29T11:31:24.879387image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T11:31:24.932398image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
019777
98.9%
1223
 
1.1%

Most occurring characters

ValueCountFrequency (%)
019777
98.9%
1223
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number20000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
019777
98.9%
1223
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
Common20000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
019777
98.9%
1223
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII20000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
019777
98.9%
1223
 
1.1%

SepsisLabel-max
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.4 KiB
0
18858 
1
 
1142

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters20000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
018858
94.3%
11142
 
5.7%

Length

2021-11-29T11:31:24.987482image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T11:31:25.041054image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
018858
94.3%
11142
 
5.7%

Most occurring characters

ValueCountFrequency (%)
018858
94.3%
11142
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number20000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
018858
94.3%
11142
 
5.7%

Most occurring scripts

ValueCountFrequency (%)
Common20000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
018858
94.3%
11142
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII20000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
018858
94.3%
11142
 
5.7%

Sepsis-min
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.4 KiB
0
18858 
1
 
1142

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters20000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
018858
94.3%
11142
 
5.7%

Length

2021-11-29T11:31:25.096051image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T11:31:25.148999image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
018858
94.3%
11142
 
5.7%

Most occurring characters

ValueCountFrequency (%)
018858
94.3%
11142
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number20000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
018858
94.3%
11142
 
5.7%

Most occurring scripts

ValueCountFrequency (%)
Common20000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
018858
94.3%
11142
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII20000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
018858
94.3%
11142
 
5.7%

Sepsis-max
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.4 KiB
0
18858 
1
 
1142

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters20000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
018858
94.3%
11142
 
5.7%

Length

2021-11-29T11:31:25.204214image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T11:31:25.257051image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
018858
94.3%
11142
 
5.7%

Most occurring characters

ValueCountFrequency (%)
018858
94.3%
11142
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number20000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
018858
94.3%
11142
 
5.7%

Most occurring scripts

ValueCountFrequency (%)
Common20000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
018858
94.3%
11142
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII20000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
018858
94.3%
11142
 
5.7%

Hours-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct230
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.09975
Minimum8
Maximum336
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:25.319122image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile14
Q123
median38
Q347
95-th percentile58
Maximum336
Range328
Interquartile range (IQR)24

Descriptive statistics

Standard deviation23.27525267
Coefficient of variation (CV)0.6109030287
Kurtosis44.03440685
Mean38.09975
Median Absolute Deviation (MAD)12
Skewness4.965291886
Sum761995
Variance541.7373868
MonotonicityNot monotonic
2021-11-29T11:31:25.418106image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
39697
 
3.5%
38667
 
3.3%
36664
 
3.3%
40651
 
3.3%
41639
 
3.2%
43610
 
3.0%
42596
 
3.0%
37591
 
3.0%
21564
 
2.8%
44563
 
2.8%
Other values (220)13758
68.8%
ValueCountFrequency (%)
8204
1.0%
9114
 
0.6%
10126
 
0.6%
11120
 
0.6%
12164
0.8%
13205
1.0%
14218
1.1%
15305
1.5%
16327
1.6%
17373
1.9%
ValueCountFrequency (%)
3365
< 0.1%
3352
 
< 0.1%
3341
 
< 0.1%
3331
 
< 0.1%
3271
 
< 0.1%
3261
 
< 0.1%
3201
 
< 0.1%
3181
 
< 0.1%
3122
 
< 0.1%
3102
 
< 0.1%

Hours-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct230
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.09975
Minimum8
Maximum336
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size156.4 KiB
2021-11-29T11:31:25.523695image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile14
Q123
median38
Q347
95-th percentile58
Maximum336
Range328
Interquartile range (IQR)24

Descriptive statistics

Standard deviation23.27525267
Coefficient of variation (CV)0.6109030287
Kurtosis44.03440685
Mean38.09975
Median Absolute Deviation (MAD)12
Skewness4.965291886
Sum761995
Variance541.7373868
MonotonicityNot monotonic
2021-11-29T11:31:25.624294image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
39697
 
3.5%
38667
 
3.3%
36664
 
3.3%
40651
 
3.3%
41639
 
3.2%
43610
 
3.0%
42596
 
3.0%
37591
 
3.0%
21564
 
2.8%
44563
 
2.8%
Other values (220)13758
68.8%
ValueCountFrequency (%)
8204
1.0%
9114
 
0.6%
10126
 
0.6%
11120
 
0.6%
12164
0.8%
13205
1.0%
14218
1.1%
15305
1.5%
16327
1.6%
17373
1.9%
ValueCountFrequency (%)
3365
< 0.1%
3352
 
< 0.1%
3341
 
< 0.1%
3331
 
< 0.1%
3271
 
< 0.1%
3261
 
< 0.1%
3201
 
< 0.1%
3181
 
< 0.1%
3122
 
< 0.1%
3102
 
< 0.1%

Interactions

Correlations

2021-11-29T11:31:25.831573image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2021-11-29T11:31:27.629573image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2021-11-29T11:31:29.346663image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2021-11-29T11:31:30.951905image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2021-11-29T11:31:02.695176image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2021-11-29T11:31:04.931484image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2021-11-29T11:31:07.506206image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

PatientIDHR-minHR-maxO2Sat-minO2Sat-maxTemp-minTemp-maxSBP-minSBP-maxMAP-minMAP-maxDBP-minDBP-maxResp-minResp-maxEtCO2-minEtCO2-maxBaseExcess-minBaseExcess-maxHCO3-minHCO3-maxFiO2-minFiO2-maxpH-minpH-maxPaCO2-minPaCO2-maxSaO2-minSaO2-maxAST-minAST-maxBUN-minBUN-maxAlkalinephos-minAlkalinephos-maxCalcium-minCalcium-maxChloride-minChloride-maxCreatinine-minCreatinine-maxBilirubin_direct-minBilirubin_direct-maxGlucose-minGlucose-maxLactate-minLactate-maxMagnesium-minMagnesium-maxPhosphate-minPhosphate-maxPotassium-minPotassium-maxBilirubin_total-minBilirubin_total-maxTroponinI-minTroponinI-maxHct-minHct-maxHgb-minHgb-maxPTT-minPTT-maxWBC-minWBC-maxFibrinogen-minFibrinogen-maxPlatelets-minPlatelets-maxAge-minAge-maxGender-minGender-maxUnit1-minUnit1-maxUnit2-minUnit2-maxHospAdmTime-minHospAdmTime-maxICULOS-minICULOS-maxSepsisLabel-minSepsisLabel-maxSepsis-minSepsis-maxHours-minHours-max
010000191.0107.092.099.036.537.0104.0123.075.089.055.072.016.023.5NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN30.030.0NaNNaN7.807.8NaNNaN1.501.50NaNNaN112.0233.0NaNNaN2.02.1NaNNaN3.704.2NaNNaNNaNNaN35.335.311.311.3NaNNaN10.810.8NaNNaN170.0170.07373111.01.00.00.0-214.64-214.6412400002424
110000256.071.594.0100.035.237.986.0157.056.095.041.071.016.026.035.039.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN17.017.0NaNNaN8.208.2NaNNaN0.840.84NaNNaN68.0222.0NaNNaN2.22.31.83.63.805.2NaNNaN3.703.7031.431.411.111.1NaNNaN13.213.2NaNNaN85.085.08383110.00.01.01.0-123.17-123.1712500002525
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